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TECHNOLOGY : JAVA

DOMAIN : IEEE TRANSACTIONS ON NETWORKING

S.NO TITLES ABSTRACT YEAR
1. Balancing the Trade- In This Project, we propose schemes to balance the trade- 2012
Offs between Query offs between data availability and query delay under
Delay and Data different system settings and requirements. Mobile nodes
Availability in in one partition are not able to access data hosted by
MANETs nodes in other partitions, and hence significantly degrade
the performance of data access. To deal with this
problem, We apply data replication techniques.
2. MeasuRouting: A In this paper we present a theoretical framework for 2012
Framework for MeasuRouting. Furthermore, as proofs-of-concept, we
Routing Assisted present synthetic and practical monitoring applications to
Traffic Monitoring showcase the utility enhancement achieved with
MeasuRouting.
3. Cooperative Profit We model Optimal cooperation using the theory of 2012
Sharing in Coalition- transferable payoff coalitional games. We show that the
Based Resource optimum cooperation strategy, which involves the
Allocation in Wireless acquisition, deployment, and allocation of the channels
Networks and base stations (to customers), can be computed as the
solution of a concave or an integer optimization. We next
show that the grand coalition is stable in many different
settings.
4. Bloom Cast: Efficient In this paper we propose Bloom Cast, an efficient and 2012
Full-Text Retrieval effective full-text retrieval scheme, in unstructured P2P
over Unstructured networks. Bloom Cast is effective because it guarantees
P2Ps with Guaranteed perfect recall rate with high probability.
Recall
5. On Optimizing We propose a novel overlay formation algorithm for 2012
Overlay Topologies unstructured P2P networks. Based on the file sharing
for Search in pattern exhibiting the power-law property, our proposal
Unstructured Peer-to- is unique in that it poses rigorous performance
Peer Networks guarantees.
6. An MDP-Based In this paper, we propose an automated Markov Decision 2012
Dynamic Optimization Process (MDP)-based methodology to prescribe optimal
Methodology for sensor node operation to meet application requirements
Wireless Sensor and adapt to changing environmental stimuli. Numerical
Networks results confirm the optimality of our proposed
methodology and reveal that our methodology more
closely meets application requirements compared to other
feasible policies.
7. Obtaining Provably In this paper, we address The Internet Topology 2012
Legitimate Internet Problems by providing a framework to generate small,
Topologies realistic, and policy-aware topologies. We propose HBR,

a novel sampling method, which exploits the inherent
hierarchy of the policy-aware Internet topology. We
formally prove that our approach generates connected
and legitimate topologies, which are compatible with the
policy-based routing conventions and rules.
8. Extrema Propagation: This paper introduces Extrema Propagation, a 2012
Fast Distributed probabilistic technique for distributed estimation of the
Estimation of Sums sum of positive real numbers. The technique relies on the
and Network Sizes exchange of duplicate insensitive messages and can be
applied in flood and/or epidemic settings, where
multipath routing occurs; it is tolerant of message loss; it
is fast, as the number of message exchange steps can be
made just slightly above the theoretical minimum; and it
is fully distributed, with no single point of failure and the
result produced at every node.
9. Latency Equalization We propose a Latency Equalization (LEQ) service, 2012
as a New Network which equalizes the perceived latency for all clients.
Service Primitive
10. Grouping-Enhanced This paper proposes a scheme, referred to as Grouping- 2012
Resilient Probabilistic enhanced Resilient Probabilistic En-route Filtering
En-Route Filtering of (GRPEF). In GRPEF, an efficient distributed algorithm is
Injected False Data in proposed to group nodes without incurring extra groups,
WSNs and a multi axis division based approach for deriving
location-aware keys is used to overcome the threshold
problem and remove the dependence on the sink
immobility and routing protocols.
11. On Achieving Group- A multicast scheme is stragegyproof if no receiver has 2012
Strategy proof incentive to lie about her true valuation. It is further
Multicast group strategyproof if no group of colluding receivers
has incentive to lie. We study multicast schemes that
target group strategyproofness, in both directed and
undirected networks.
12. Distributed -Optimal In this paper, we develop a framework for user 2012
User Association and association in infrastructure-based wireless networks,
Cell Load Balancing specifically focused on flow-level cell load balancing
in Wireless Networks under spatially in homogeneous traffic distributions. Our
work encompasses several different user association
policies: rate-optimal, throughput-optimal, delay-optimal,
and load-equalizing, which we collectively denote ?-
optimal user association.
13. Opportunistic Flow- In this paper, we propose Consistent Net Flow (CNF) 2012
Level Latency architecture for measuring per-flow delay measurements
Estimation Using within routers. CNF utilizes the existing Net Flow
Consistent Net Flow architecture that already reports the first and last
timestamps per flow, and it proposes hash-based
sampling to ensure that two adjacent routers record the

same flows.
14. Leveraging a Resource discovery is critical to the usability and 2012
Compound Graph- accessibility of grid computing systems. Distributed
Based DHT for Multi- Hash Table (DHT) has been applied to grid systems as a
Attribute Range distributed mechanism for providing scalable range-
Queries with query and multi-attribute resource discovery. Multi-
Performance Analysis DHT-based approaches depend on multiple DHT
networks with each network responsible for a single
attribute. Single-DHT-based approaches keep the
resource information of all attributes in a single node.
Both classes of approaches lead to high overhead. In this
paper, we propose a Low-Overhead Range-query Multi-
attribute (LORM) DHT-based resource discovery
approach. Unlike other DHT-based approaches, LORM
relies on a single compound graph-based DHT network
and distributes resource information among nodes in
balance by taking advantage of the compound graph
structure. Moreover, it has high capability to handle the
large-scale and dynamic characteristics of resources in
grids. Experimental results demonstrate the efficiency of
LORM in comparison with other resource discovery
approaches. LORM dramatically reduces maintenance
and resource discovery overhead. In addition, it yields
significant improvements in resource location efficiency.
We also analyze the performance of the LORM approach
rigorously by comparing it with other multi-DHT-based
and single-DHT-based approaches with respect to their
overhead and efficiency. The analytical results are
consistent with experimental results, and prove the
superiority of the LORM approach in theory
15. Exploiting Excess Excess capacity (EC) is the unused capacity in a 2012
Capacity to Improve network. We propose EC management techniques to
Robustness of WDM improve network performance. Our techniques exploit
Mesh Networks the EC in two ways. First, a connection preprovisioning
algorithm is used to reduce the connection setup time.
Second, whenever possible, we use protection schemes
that have higher availability and shorter protection
switching time. Specifically, depending on the amount of
EC available in the network, our proposed EC
management techniques dynamically migrate
connections between high-availability, high-backup-
capacity protection schemes and low-availability, low-
backup-capacity protection schemes. Thus, multiple
protection schemes can coexist in the network. The four
EC management techniques studied in this paper differ in
two respects: when the connections are migrated from

one protection scheme to another, and which connections
are migrated. Specifically, Lazy techniques migrate
connections only when necessary, whereas Proactive
techniques migrate connections to free up capacity in
advance. Partial Backup Reprovisioning (PBR)
techniques try to migrate a minimal set of connections,
whereas Global Backup Reprovisioning (GBR)
techniques migrate all connections. We develop integer
linear program (ILP) formulations and heuristic
algorithms for the EC management techniques. We then
present numerical examples to illustrate how the EC
management techniques improve network performance
by exploiting the EC in wavelength-division-
multiplexing (WDM) mesh networks
16. Revisiting Dynamic In unstructured peer-to-peer networks, the average 2012
Query Protocols in response latency and traffic cost of a query are two main
Unstructured Peer-to- performance metrics. Controlled-flooding resource query
Peer Networks algorithms are widely used in unstructured networks such
as peer-to-peer networks. In this paper, we propose a
novel algorithm named Selective Dynamic Query (SDQ).
Based on mathematical programming, SDQ calculates
the optimal combination of an integer TTL value and a
set of neighbors to control the scope of the next query.
Our results demonstrate that SDQ provides finer grained
control than other algorithms: its response latency is
close to the well-known minimum one via Expanding
Ring; in the mean time, its traffic cost is also close to the
minimum. To our best knowledge, this is the first work
capable of achieving a best trade-off between response
latency and traffic cost.

17. Adaptive A distributed adaptive opportunistic routing scheme for 2012
Opportunistic Routing multihop wireless ad hoc networks is proposed. The
for Wireless Ad Hoc proposed scheme utilizes a reinforcement learning
Networks framework to opportunistically route the packets even in
the absence of reliable knowledge about channel
statistics and network model. This scheme is shown to be
optimal with respect to an expected average per-packet
reward criterion. The proposed routing scheme jointly
addresses the issues of learning and routing in an
opportunistic context, where the network structure is
characterized by the transmission success probabilities.
In particular, this learning framework leads to a
stochastic routing scheme that optimally “explores” and
“exploits” the opportunities in the network.
18. Design, This load balancer improves both throughput and 2012

Implementation, and response time versus a single node, while exposing a
Performance of A single interface to external clients. The algorithm
Load Balancer for SIP achieves Transaction Least-Work-Left (TLWL),
Server Clusters – achieves its performance by integrating several features:
projects 2012 knowledge of the SIP protocol; dynamic estimates of
back-end server load; distinguishing transactions from
calls; recognizing variability in call length; and
exploiting differences in processing costs for different
SIP transactions.
19. Router Support for An increasing number of datacenter network 2012
Fine-Grained Latency applications, including automated trading and high-
Measurements – performance computing, have stringent end-to-end
projects 2012 latency requirements where even microsecond variations
may be intolerable. The resulting fine-grained
measurement demands cannot be met effectively by
existing technologies, such as SNMP, NetFlow, or active
probing. Instrumenting routers with a hash-based
primitive has been proposed that called as Lossy
Difference Aggregator (LDA) to measure latencies down
to tens of microseconds even in the presence of packet
loss. Because LDA does not modify or encapsulate the
packet, it can be deployed incrementally without changes
along the forwarding path. When compared to Poisson-
spaced active probing with similar overheads, LDA
mechanism delivers orders of magnitude smaller relative
error. Although ubiquitous deployment is ultimately
desired, it may be hard to achieve in the shorter term
20. A Framework for Monitoring transit traffic at one or more points in a 2012
Routing Assisted network is of interest to network operators for reasons of
Traffic Monitoring – traffic accounting, debugging or troubleshooting,
projects 2012 forensics, and traffic engineering. Previous research in
the area has focused on deriving a placement of monitors
across the network towards the end of maximizing the
monitoring utility of the network operator for a given
traffic routing. However, both traffic characteristics and
measurement objectives can dynamically change over
time, rendering a previously optimal placement of
monitors suboptimal. It is not feasible to dynamically
redeploy/reconfigure measurement infrastructure to cater
to such evolving measurement requirements. This
problem is addressed by strategically routing traffic sub-
populations over fixed monitors. This approach is
MeasuRouting. The main challenge for MeasuRouting is
to work within the constraints of existing intra-domain
traffic engineering operations that are geared for
efficiently utilizing bandwidth resources, or meeting

Quality of Service (QoS) constraints, or both. A
fundamental feature of intra-domain routing, that makes
MeasuRouting feasible, is that intra-domain routing is
often specified for aggregate flows. MeasuRouting, can
therefore, differentially route components of an
aggregate flow while ensuring that the aggregate
placement is compliant to original traffic engineering
objectives.
21. Independent In order to achieve resilient multipath routing we 2012
Directed Acyclic introduce the concept of Independent Directed Acyclic
Graphs for Resilient Graphs (IDAGs) in this study. Link-independent (Node-
Multipath Routing independent) DAGs satisfy the property that any path
from a source to the root on one DAG is link-disjoint
(node-disjoint) with any path from the source to the root
on the other DAG. Given a network, we develop
polynomial time algorithms to compute link-independent
and node-independent DAGs. The algorithm developed
in this paper: (1) provides multipath routing; (2) utilizes
all possible edges; (3) guarantees recovery from single
link failure; and (4) achieves all these with at most one
bit per packet as overhead when routing is based on
destination address and incoming edge. We show the
effectiveness of the proposed IDAGs approach by
comparing key performance indices to that of the
independent trees and multiple pairs of independent trees
techniques through extensive simulations
22. A Greedy Link Information-theoretic broadcast channels (BCs) and 2012
Scheduler for Wireless multiple-access channels (MACs) enable a single node to
Networks With transmit data simultaneously to multiple nodes, and
Gaussian Multiple- multiple nodes to transmit data simultaneously to a single
Access and Broadcast node, respectively. In this paper, we address the problem
Channels of link scheduling in multihop wireless networks
containing nodes with BC and MAC capabilities. We
first propose an interference model that extends protocol
interference models, originally designed for point-to-
point channels, to include the possibility of BCs and
MACs. Due to the high complexity of optimal link
schedulers, we introduce the Multiuser Greedy
Maximum Weight algorithm for link scheduling in
multihop wireless networks containing BCs and MACs.
Given a network graph, we develop new local pooling
conditions and show that the performance of our
algorithm can be fully characterized using the associated
parameter, the multiuser local pooling factor. We provide
examples of some network graphs, on which we apply
local pooling conditions and derive the multiuser local

pooling factor. We prove optimality of our algorithm in
tree networks and show that the exploitation of BCs and
MACs improve the throughput performance considerably
in multihop wireless networks.

23. A Quantization We consider rate optimization in multicast systems that 2012
Theoretic Perspective use several multicast trees on a communication network.
on Simulcast and The network is shared between different applications. For
Layered Multicast that reason, we model the available bandwidth for
Optimization multicast as stochastic. For specific network topologies,
we show that the multicast rate optimization problem is
equivalent to the optimization of scalar quantization. We
use results from rate-distortion theory to provide a bound
on the achievable performance for the multicast rate
optimization problem. A large number of receivers
makes the possibility of adaptation to changing network
conditions desirable in a practical system. To this end,
we derive an analytical solution to the problem that is
asymptotically optimal in the number of multicast trees.
We derive local optimality conditions, which we use to
describe a general class of iterative algorithms that give
locally optimal solutions to the problem. Simulation
results are provided for the multicast of an i.i.d. Gaussian
process, an i.i.d. Laplacian process, and a video source.
24. Bit Weaving A Non- Ternary Content Addressable Memories (TCAMs) have 2012
Prefix Approach to become the de facto standard in industry for fast packet
Compressing Packet classification. Unfortunately, TCAMs have limitations of
Classifiers in TCAMs small capacity, high power consumption, high heat
generation, and high cost. The well-known range
expansion problem exacerbates these limitations as each
classifier rule typically has to be converted to multiple
TCAM rules. One method for coping with these
limitations is to use compression schemes to reduce the
number of TCAM rules required to represent a classifier.
Unfortunately, all existing compression schemes only
produce prefix classifiers. Thus, they all miss the
compression opportunities created by non-prefix ternary
classifiers.
25. Cooperative Profit We consider a network in which several service 2012
Sharing in Coalition- providers offer wireless access service to their respective
Based Resource subscribed customers through potentially multi-hop
Allocation in Wireless routes. If providers cooperate, i.e., pool their resources,
Networks such as spectrum and base stations, and agree to serve
each others' customers, their aggregate payoffs, and
individual shares, can potentially substantially increase
through efficient utilization of resources and statistical

multiplexing. The potential of such cooperation can
however be realized only if each provider intelligently
determines who it would cooperate with, when it would
cooperate, and how it would share its resources during
such cooperation. Also, when the providers share their
aggregate revenues, developing a rational basis for such
sharing is imperative for the stability of the coalitions.
We model such cooperation using transferable payoff
coalitional game theory. We first consider the scenario
that locations of the base stations and the channels that
each provider can use have already been decided apriori.
We show that the optimum cooperation strategy, which
involves the allocations of the channels and the base
stations to mobile customers, can be obtained as
solutions of convex optimizations. We next show that the
grand coalition is stable in this case, i.e. if all providers
cooperate, there is always an operating point that
maximizes the providers' aggregate payoff, while
offering each such a share that removes any incentive to
split from the coalition. Next, we show that when the
providers can choose the locations of their base stations
and decide which channels to acquire, the above results
hold in important special cases. Finally, we examine
cooperation when providers do not share their payoffs,
but still share their resources so as to enhance individual
payoffs. We show that the grand coalition continues to be
stable.
26. CSMACN Carrier A wireless transmitter learns of a packet loss and infers 2012
Sense Multiple Access collision only after completing the entire transmission. If
With Collision the transmitter could detect the collision early [such as
Notification with carrier sense multiple access with collision detection
(CSMA/CD) in wired networks], it could immediately
abort its transmission, freeing the channel for useful
communication. There are two main hurdles to realize
CSMA/CD in wireless networks. First, a wireless
transmitter cannot simultaneously transmit and listen for
a collision. Second, any channel activity around the
transmitter may not be an indicator of collision at the
receiver. This paper attempts to approximate CSMA/CD
in wireless networks with a novel scheme called
CSMA/CN (collision notification). Under CSMA/CN,
the receiver uses PHY-layer information to detect a
collision and immediately notifies the transmitter. The
collision notification consists of a unique signature, sent
on the same channel as the data. The transmitter employs
a listener antenna and performs signature correlation to

discern this notification. Once discerned, the transmitter
immediately aborts the transmission. We show that the
notification signature can be reliably detected at the
listener antenna, even in the presence of a strong self-
interference from the transmit antenna. A prototype
testbed of 10 USRP/GNU Radios demonstrates the
feasibility and effectiveness of CSMA/CN.

27. Dynamic Power A major problem in wireless networks is coping with 2012
Allocation Under limited resources, such as bandwidth and energy. These
Arbitrary Varying issues become a major algorithmic challenge in view of
Channels—An Online the dynamic nature of the wireless domain. We consider
Approach in this paper the single-transmitter power assignment
problem under time-varying channels, with the objective
of maximizing the data throughput. It is assumed that the
transmitter has a limited power budget, to be sequentially
divided during the lifetime of the battery. We deviate
from the classic work in this area, which leads to explicit
"water-filling" solutions, by considering a realistic
scenario where the channel state quality changes
arbitrarily from one transmission to the other. The
problem is accordingly tackled within the framework of
competitive analysis, which allows for worst case
performance guarantees in setups with arbitrarily varying
channel conditions. We address both a "discrete" case,
where the transmitter can transmit only at a fixed power
level, and a "continuous" case, where the transmitter can
choose any power level out of a bounded interval. For
both cases, we propose online power-allocation
algorithms with proven worst-case performance bounds.
In addition, we establish lower bounds on the worst-case
performance of any online algorithm, and show that our
proposed algorithms are optimal.
28. Economic Issues in In designing and managing a shared infrastructure, one 2012
Shared Infrastructures must take account of the fact that its participants will
make self-interested and strategic decisions about the
resources that they are willing to contribute to it and/or
the share of its cost that they are willing to bear. Taking
proper account of the incentive issues that thereby arise,
we design mechanisms that, by eliciting appropriate
information from the participants, can obtain for them
maximal social welfare, subject to charging payments
that are sufficient to cover costs. We show that there are
incentivizing roles to be played both by the payments
that we ask from the participants and the specification of
how resources are to be shared. New in this paper is our

formulation of models for designing optimal
management policies, our analysis that demonstrates the
inadequacy of simple sharing policies, and our proposals
for some better ones. We learn that simple policies may
be far from optimal and that efficient policy design is not
trivial. However, we find that optimal policies have
simple forms in the limit as the number of participants
becomes large.
29. On New Approaches Society relies heavily on its networked physical 2012
of Assessing Network infrastructure and information systems. Accurately
Vulnerability assessing the vulnerability of these systems against
Hardness and disruptive events is vital for planning and risk
Approximation management. Existing approaches to vulnerability
assessments of large-scale systems mainly focus on
investigating inhomogeneous properties of the
underlying graph elements. These measures and the
associated heuristic solutions are limited in evaluating
the vulnerability of large-scale network topologies.
Furthermore, these approaches often fail to provide
performance guarantees of the proposed solutions. In this
paper, we propose a vulnerability measure, pairwise
connectivity, and use it to formulate network
vulnerability assessment as a graph-theoretical
optimization problem, referred to as -disruptor. The
objective is to identify the minimum set of critical
network elements, namely nodes and edges, whose
removal results in a specific degradation of the network
global pairwise connectivity. We prove the NP-
completeness and inapproximability of this problem and
propose an pseudo-approximation algorithm to
computing the set of critical nodes and an pseudo-
approximation algorithm for computing the set of critical
edges. The results of an extensive simulation-based
experiment show the feasibility of our proposed
vulnerability assessment framework and the efficiency of
the proposed approximation algorithms in comparison to
other approaches.
30. Quantifying Video- With the proliferation of multimedia content on the 2012
QoE Degradations of Internet, there is an increasing demand for video streams
Internet Links with high perceptual quality. The capability of present-
day Internet links in delivering high-perceptual-quality
streaming services, however, is not completely
understood. Link-level degradations caused by
intradomain routing policies and inter-ISP peering
policies are hard to obtain, as Internet service providers
often consider such information proprietary.

Understanding link-level degradations will enable us in
designing future protocols, policies, and architectures to
meet the rising multimedia demands. This paper presents
a trace-driven study to understand quality-of-experience
(QoE) capabilities of present-day Internet links using 51
diverse ISPs with a major presence in the US, Europe,
and Asia-Pacific. We study their links from 38 vantage
points in the Internet using both passive tracing and
active probing for six days. We provide the first
measurements of link-level degradations and case studies
of intra-ISP and inter-ISP peering links from a
multimedia standpoint. Our study offers surprising
insights into intradomain traffic engineering, peering link
loading, BGP, and the inefficiencies of using
autonomous system (AS)-path lengths as a routing
metric. Though our results indicate that Internet routing
policies are not optimized for delivering high-perceptual-
quality streaming services, we argue that alternative
strategies such as overlay networks can help meet QoE
demands over the Internet. Streaming services apart, our
Internet measurement results can be used as an input to a
variety of research problems.

31. Order Matters Modern wireless interfaces support a physical-layer 2012
Transmission capability called Message in Message (MIM). Briefly,
Reordering in MIM allows a receiver to disengage from an ongoing
Wireless Networks reception and engage onto a stronger incoming signal.
Links that otherwise conflict with each other can be
made concurrent with MIM. However, the concurrency is
not immediate and can be achieved only if conflicting
links begin transmission in a specific order. The
importance of link order is new in wireless research,
motivating MIM-aware revisions to link-scheduling
protocols. This paper identifies the opportunity in MIM-
aware reordering, characterizes the optimal improvement
in throughput, and designs a link-layer protocol for
enterprise wireless LANs to achieve it. Testbed and
simulation results confirm the performance gains of the
proposed system.
32. Static Routing and In this paper, we investigate the static multicast advance 2012
Wavelength reservation (MCAR) problem for all-optical wavelength-
Assignment for routed WDM networks. Under the advanced reservation
Multicast Advance traffic model, connection requests specify their start time
Reservation in All- to be some time in the future and also specify their
Optical Wavelength- holding times. We investigate the static MCAR problem
Routed WDM where the set of advance reservation requests is known

Networks ahead of time. We prove the MCAR problem is NP-
complete, formulate the problem mathematically as an
integer linear program (ILP), and develop three efficient
heuristics, seqRWA, ISH, and SA, to solve the problem
for practical size networks. We also introduce a
theoretical lower bound on the number of wavelengths
required. To evaluate our heuristics, we first compare
their performances to the ILP for small networks, and
then simulate them over real-world, large-scale networks.
We find the SA heuristic provides close to optimal
results compared to the ILP for our smaller networks, and
up to a 33% improvement over seqRWA and up to a 22%
improvement over ISH on realistic networks. SA
provides, on average, solutions 1.5-1.8 times the cost
given by our conservative lower bound on large
networks.
33. System-Level We consider a robust-optimization-driven system-level 2012
Optimization in approach to interference management in a cellular
Wireless Networks broadband system operating in an interference-limited
Managing Interference and highly dynamic regime. Here, base stations in
and Uncertainty via neighboring cells (partially) coordinate their transmission
Robust Optimization schedules in an attempt to avoid simultaneous max-
power transmission to their mutual cell edge. Limits on
communication overhead and use of the backhaul require
base station coordination to occur at a slower timescale
than the customer arrival process. The central challenge
is to properly structure coordination decisions at the slow
timescale, as these subsequently restrict the actions of
each base station until the next coordination period.
Moreover, because coordination occurs at the slower
timescale, the statistics of the arriving customers, e.g.,
the load, are typically only approximately known-thus,
this coordination must be done with only approximate
knowledge of statistics. We show that performance of
existing approaches that assume exact knowledge of
these statistics can degrade rapidly as the uncertainty in
the arrival process increases. We show that a two-stage
robust optimization framework is a natural way to model
two-timescale decision problems. We provide tractable
formulations for the base-station coordination problem
and show that our formulation is robust to fluctuations
(uncertainties) in the arriving load. This tolerance to load
fluctuation also serves to reduce the need for frequent
reoptimization across base stations, thus helping
minimize the communication overhead required for
system-level interference reduction. Our robust

optimization formulations are flexible, allowing us to
control the conservatism of the solution. Our simulations
show that we can build in robustness without significant
degradation of nominal performance.
34. The Case for Feed- Variable latencies due to communication delays or 2012
Forward Clock system noise is the central challenge faced by time-
Synchronization keeping algorithms when synchronizing over the
network. Using extensive experiments, we explore the
robustness of synchronization in the face of both normal
and extreme latency variability and compare the
feedback approaches of ntpd and ptpd (a software
implementation of IEEE-1588) to the feed-forward
approach of the RADclock and advocate for the benefits
of a feed-forward approach. Noting the current lack of
kernel support, we present extensions to existing
mechanisms in the Linux and FreeBSD kernels giving
full access to all available raw counters, and then
evaluate the TSC, HPET, and ACPI counters' suitability
as hardware timing sources. We demonstrate how the
RADclock achieves the same microsecond accuracy with
each counter.

TECHNOLOGY : JAVA

DOMAIN : IEEE TRANSACTIONS ON NETWORK SECURITY

1. Design and We have designed and implemented TARF, a robust 2012
Implementation of trust-aware routing framework for dynamic wireless
TARF: A Trust-Aware sensor networks (WSN). Without tight time
Routing Framework synchronization or known Geographic information,
for WSNs TARF provides trustworthy and energy-efficient route.
Most importantly, TARF proves effective against those
harmful attacks developed out of identity deception; the
resilience of TARF is verified through extensive
evaluation with both simulation and empirical
experiments on large-scale WSNs under various
scenarios including mobile and RF-shielding network
conditions.
2. Risk-Aware In this paper, we propose a risk-aware response 2012
Mitigation for mechanism to systematically Cope with the identified
MANET Routing routing attacks. Our risk-aware approach is based on an
Attacks extended Dempster-Shafer mathematical theory of

Evidence introducing a notion of importance factors.
3. Survivability In this paper, we study survivability issues for RFID. We 2012
Experiment and first present an RFID survivability experiment to define a
Attack foundation to measure the degree of survivability of an
Characterization for RFID system under varying attacks. Then we model a
RFID series of malicious scenarios using stochastic process
algebras and study the different effects of those attacks
on the ability of the RFID system to provide critical
services even when parts of the system have been
damaged.
4. Detecting and In this paper, we represent an 2012
Resolving Firewall innovative policy anomaly management framework
Policy Anomalies for firewalls, adopting a rule-based segmentation
technique to identify policy anomalies and derive
effective anomaly resolutions. In particular, we articulate
a grid-based representation technique, providing an
intuitive cognitive sense about policy anomaly.
5. Automatic In this paper, we present a complete solution for 2012
Reconfiguration for dynamically changing system membership in a large-
Large-Scale Reliable scale Byzantine-fault-tolerant system. We present a
Storage Systems service that tracks system membership and periodically
notifies other system nodes of changes.
6. Detecting Anomalous In this paper, we introduce the community anomaly 2012
Insiders in detection system (CADS), an unsupervised learning
Collaborative framework to detect insider threats based on the access
Information Systems logs of collaborative environments. The framework is
based on the observation that typical CIS users tend to
form community structures based on the subjects
accessed
7. An Extended Visual Conventional visual secret sharing schemes generate 2012
Cryptography noise-like random pixels on shares to hide secret images.
Algorithm for General It suffers a management problem. In this paper, we
Access Structures propose a general approach to solve the above-
mentioned problems; the approach can be used for binary
secret images in non computer-aided decryption
environments.
8. Mitigating Distributed In this paper, we extend port-hopping to support 2012
Denial of Service multiparty applications, by proposing the BIGWHEEL
Attacks in Multiparty algorithm, for each application server to communicate
Applications in the with multiple clients in a port-hopping manner without
Presence of Clock the need for group synchronization. Furthermore, we
Drift present an adaptive algorithm, HOPERAA, for enabling
hopping in the presence of bounded asynchrony, namely,
when the communicating parties have clocks with clock
drifts.
9. On the Security and Content distribution via network coding has received a 2012

Efficiency of Content lot of attention lately. However, direct application of
Distribution via network coding may be insecure. In particular, attackers
Network Coding can inject "bogus” data to corrupt the content distribution
process so as to hinder the information dispersal or even
deplete the network resource. Therefore, content
verification is an important and practical issue when
network coding is employed.
10. Packet-Hiding In this paper, we address the problem of selective 2012
Methods for jamming attacks in wireless networks. In these attacks,
Preventing Selective the adversary is active only for a short period of time,
Jamming Attacks selectively targeting messages of high importance.
11. Stochastic Model of 2012
Multi virus Dynamics
12. Peering Equilibrium Our scheme relies on a game theory modeling, with a 2012
Multipath Routing: A non-cooperative potential game considering both routing
Game Theory and congestions costs. We compare different PEMP
Framework for policies to BGP Multipath schemes by emulating a
Internet Peering realistic peering scenario.
Settlements
13. Modeling and Our scheme uses the Power Spectral Density (PSD) 2012
Detection of distribution of the scan traffic volume and its
Camouflaging Worm corresponding Spectral Flatness Measure (SFM) to
distinguish the C-Worm traffic from background traffic.
The performance data clearly demonstrates that our
scheme can effectively detect the C-Worm
propagation.two heuristic algorithms for the two sub
problems.
14. Analysis of a Botnet We present the design of an advanced hybrid peer-to- 2012
Takeover peer botnet. Compared with current botnets, the proposed
botnet is harder to be shut down, monitored, and
hijacked. It provides individualized encryption and
control traffic dispersion.
15. Efficient Network As real-time traffic such as video or voice increases on 2012
Modification to the Internet, ISPs are required to provide stable quality as
Improve QoS Stability well as connectivity at failures. For ISPs, how to
at Failures effectively improve the stability of these qualities at
failures with the minimum investment cost is an
important issue, and they need to effectively select a
limited number of locations to add link facilities.
16. Detecting Spam Compromised machines are one of the key security 2012
Zombies by threats on the Internet; they are often used to launch
Monitoring Outgoing various security attacks such as spamming and spreading
Messages malware, DDoS, and identity theft. Given that spamming
provides a key economic incentive for attackers to recruit
the large number of compromised machines, we focus on
the detection of the compromised machines in a network

that are involved in the spamming activities, commonly
known as spam zombies. We develop an effective spam
zombie detection system named SPOT by monitoring
outgoing messages of a network. SPOT is designed based
on a powerful statistical tool called Sequential
Probability Ratio Test, which has bounded false positive
and false negative error rates. In addition, we also
evaluate the performance of the developed SPOT system
using a two-month e-mail trace collected in a large US
campus network. Our evaluation studies show that SPOT
is an effective and efficient system in automatically
detecting compromised machines in a network. For
example, among the 440 internal IP addresses observed
in the e-mail trace, SPOT identifies 132 of them as being
associated with compromised machines. Out of the 132
IP addresses identified by SPOT, 126 can be either
independently confirmed (110) or highly likely (16) to be
compromised. Moreover, only seven internal IP
addresses associated with compromised machines in the
trace are missed by SPOT. In addition, we also compare
the performance of SPOT with two other spam zombie
detection algorithms based on the number and percentage
of spam messages originated or forwarded by internal
machines, respectively, and show that SPOT outperforms
these two detection algorithms.

17. A Hybrid Approach to Real-world entities are not always represented by the 2012
Private Record same set of features in different data sets. Therefore,
Matching Network matching records of the same real-world entity
Security 2012 Java distributed across these data sets is a challenging task. If
the data sets contain private information, the problem
becomes even more difficult. Existing solutions to this
problem generally follow two approaches: sanitization
techniques and cryptographic techniques. We propose a
hybrid technique that combines these two approaches and
enables users to trade off between privacy, accuracy, and
cost. Our main contribution is the use of a blocking phase
that operates over sanitized data to filter out in a privacy-
preserving manner pairs of records that do not satisfy the
matching condition. We also provide a formal definition
of privacy and prove that the participants of our protocols
learn nothing other than their share of the result and what
can be inferred from their share of the result, their input
and sanitized views of the input data sets (which are
considered public information). Our method incurs
considerably lower costs than cryptographic techniques

and yields significantly more accurate matching results
compared to sanitization techniques, even when privacy
requirements are high.
18. ES-MPICH2: A An increasing number of commodity clusters are 2012
Message Passing connected to each other by public networks, which have
Interface with become a potential threat to security sensitive parallel
Enhanced Security applications running on the clusters. To address this
Network Security security issue, we developed a Message Passing Interface
2012 Java (MPI) implementation to preserve confidentiality of
messages communicated among nodes of clusters in an
unsecured network. We focus on MPI rather than other
protocols, because MPI is one of the most popular
communication protocols for parallel computing on
clusters. Our MPI implementation—called ES-
MPICH2—was built based on MPICH2 developed by the
Argonne National Laboratory. Like MPICH2, ES-
MPICH2 aims at supporting a large variety of
computation and communication platforms like
commodity clusters and high-speed networks. We
integrated encryption and decryption algorithms into the
MPICH2 library with the standard MPI interface and;
thus, data confidentiality of MPI applications can be
readily preserved without a need to change the source
codes of the MPI applications. MPI-application
programmers can fully configure any confidentiality
services in MPICHI2, because a secured configuration
file in ES-MPICH2 offers the programmers flexibility in
choosing any cryptographic schemes and keys
seamlessly incorporated in ES-MPICH2. We used the
Sandia Micro Benchmark and Intel MPI Benchmark
suites to evaluate and compare the performance of ES-
MPICH2 with the original MPICH2 version. Our
experiments show that overhead incurred by the
confidentiality services in ES-MPICH2 is marginal for
small messages. The security overhead in ES-MPICH2
becomes more pronounced with larger messages. Our
results also show that security overhead can be
significantly reduced in ES-MPICH2 by high-
performance clusters.
19. Ensuring Distributed Cloud computing enables highly scalable services to be 2012
Accountability for easily consumed over the Internet on an as-needed basis.
Data Sharing in the A major feature of the cloud services is that users’ data
Cloud are usually processed remotely in unknown machines
that users do not own or operate. While enjoying the
convenience brought by this new emerging technology,
users’ fears of losing control of their own data

(particularly, financial and health data) can become a
significant barrier to the wide adoption of cloud services.
To address this problem, here, we propose a novel highly
decentralized information accountability framework to
keep track of the actual usage of the users’ data in the
cloud. In particular, we propose an object-centered
approach that enables enclosing our logging mechanism
together with users’ data and policies. We leverage the
JAR programmable capabilities to both create a dynamic
and traveling object, and to ensure that any access to
users’ data will trigger authentication and automated
logging local to the JARs. To strengthen user’s control,
we also provide distributed auditing mechanisms. We
provide extensive experimental studies that demonstrate
the efficiency and effectiveness of the proposed
approaches.
20. BECAN: A Injecting false data attack is a well known serious threat 2012
Bandwidth-Efficient to wireless sensor network, for which an adversary
Cooperative reports bogus information to sink causing error decision
Authentication at upper level and energy waste in en-route nodes. In this
Scheme for Filtering paper, we propose a novel bandwidth-efficient
Injected False Data in cooperative authentication (BECAN) scheme for filtering
Wireless Sensor injected false data. Based on the random graph
Networks – projects characteristics of sensor node deployment and the
2012 cooperative bit-compressed authentication technique, the
proposed BECAN scheme can save energy by early
detecting and filtering the majority of injected false data
with minor extra overheads at the en-route nodes. In
addition, only a very small fraction of injected false data
needs to be checked by the sink, which thus largely
reduces the burden of the sink. Both theoretical and
simulation results are given to demonstrate the
effectiveness of the proposed scheme in terms of high
filtering probability and energy saving.
21. A Flexible Approach There is an increasing need for fault tolerance 2012
to Improving System capabilities in logic devices brought about by the scaling
Reliability with of transistors to ever smaller geometries. This paper
Virtual Lockstep presents a hypervisor-based replication approach that can
be applied to commodity hardware to allow for virtually
lockstepped execution. It offers many of the benefits of
hardware-based lockstep while being cheaper and easier
to implement and more flexible in the configurations
supported. A novel form of processor state fingerprinting
is also presented, which can significantly reduce the fault
detection latency. This further improves reliability by
triggering rollback recovery before errors are recorded to

a checkpoint. The mechanisms are validated using a full
prototype and the benchmarks considered indicate an
average performance overhead of approximately 14
percent with the possibility for significant optimization.
Finally, a unique method of using virtual lockstep for
fault injection testing is presented and used to show that
significant detection latency reduction is achievable by
comparing only a small amount of data across replicas
22. A Learning-Based Despite the conventional wisdom that proactive security 2012
Approach to Reactive is superior to reactive security, we show that reactive
Security security can be competitive with proactive security as
long as the reactive defender learns from past attacks
instead of myopically overreacting to the last attack. Our
game-theoretic model follows common practice in the
security literature by making worst case assumptions
about the attacker: we grant the attacker complete
knowledge of the defender's strategy and do not require
the attacker to act rationally. In this model, we bound the
competitive ratio between a reactive defense algorithm
(which is inspired by online learning theory) and the best
fixed proactive defense. Additionally, we show that,
unlike proactive defenses, this reactive strategy is robust
to a lack of information about the attacker's incentives
and knowledge
23. Automated Security Despite the conventional wisdom that proactive security 2012
Test Generation with is superior to reactive security, we show that reactive
Formal Threat Models security can be competitive with proactive security as
long as the reactive defender learns from past attacks
instead of myopically overreacting to the last attack. Our
game-theoretic model follows common practice in the
security literature by making worst case assumptions
about the attacker: we grant the attacker complete
knowledge of the defender's strategy and do not require
the attacker to act rationally. In this model, we bound the
competitive ratio between a reactive defense algorithm
(which is inspired by online learning theory) and the best
fixed proactive defense. Additionally, we show that,
unlike proactive defenses, this reactive strategy is robust
to a lack of information about the attacker's incentives
and knowledge.

24. Automatic Byzantine-fault-tolerant replication enhances the 2012
Reconfiguration for availability and reliability of Internet services that store
Large-Scale Reliable critical state and preserve it despite attacks or software
Storage Systems errors. However, existing Byzantine-fault-tolerant
storage systems either assume a static set of replicas, or

have limitations in how they handle reconfigurations
(e.g., in terms of the scalability of the solutions or the
consistency levels they provide). This can be problematic
in long-lived, large-scale systems where system
membership is likely to change during the system
lifetime. In this paper, we present a complete solution for
dynamically changing system membership in a large-
scale Byzantine-fault-tolerant system. We present a
service that tracks system membership and periodically
notifies other system nodes of membership changes. The
membership service runs mostly automatically, to avoid
human configuration errors; is itself Byzantine-fault-
tolerant and reconfigurable; and provides applications
with a sequence of consistent views of the system
membership. We demonstrate the utility of this
membership service by using it in a novel distributed
hash table called dBQS that provides atomic semantics
even across changes in replica sets. dBQS is interesting
in its own right because its storage algorithms extend
existing Byzantine quorum protocols to handle changes
in the replica set, and because it differs from previous
DHTs by providing Byzantine fault tolerance and
offering strong semantics. We implemented the
membership service and dBQS. Our results show that the
approach works well, in practice: the membership service
is able to manage a large system and the cost to change
the system membership is low.
25. JS-Reduce Defending Web queries, credit card transactions, and medical 2012
Your Data from records are examples of transaction data flowing in
Sequential corporate data stores, and often revealing associations
Background between individuals and sensitive information. The serial
Knowledge Attacks release of these data to partner institutions or data
analysis centers in a nonaggregated form is a common
situation. In this paper, we show that correlations among
sensitive values associated to the same individuals in
different releases can be easily used to violate users'
privacy by adversaries observing multiple data releases,
even if state-of-the-art privacy protection techniques are
applied. We show how the above sequential background
knowledge can be actually obtained by an adversary, and
used to identify with high confidence the sensitive values
of an individual. Our proposed defense algorithm is
based on Jensen-Shannon divergence; experiments show
its superiority with respect to other applicable solutions.
To the best of our knowledge, this is the first work that
systematically investigates the role of sequential

background knowledge in serial release of transaction
data.

26. Mitigating DistributedNetwork-based applications commonly open some 2012
Denial of Service known communication port(s), making themselves easy
Attacks in Multiparty targets for (distributed) Denial of Service (DoS) attacks.
Applications in the Earlier solutions for this problem are based on port-
Presence of Clock hopping between pairs of processes which are
Drifts synchronous or exchange acknowledgments. However,
acknowledgments, if lost, can cause a port to be open for
longer time and thus be vulnerable, while time servers
can become targets to DoS attack themselves. Here, we
extend port-hopping to support multiparty applications,
by proposing the BIGWHEEL algorithm, for each
application server to communicate with multiple clients
in a port-hopping manner without the need for group
synchronization. Furthermore, we present an adaptive
algorithm, HOPERAA, for enabling hopping in the
presence of bounded asynchrony, namely, when the
communicating parties have clocks with clock drifts. The
solutions are simple, based on each client interacting
with the server independently of the other clients,
without the need of acknowledgments or time server(s).
Further, they do not rely on the application having a
fixed port open in the beginning, neither do they require
the clients to get a "first-contact” port from a third party.
We show analytically the properties of the algorithms
and also study experimentally their success rates,
confirm the relation with the analytical bounds.
27. On the Security and Content distribution via network coding has received a 2012
Efficiency of Content lot of attention lately. However, direct application of
Distribution via network coding may be insecure. In particular, attackers
Network Coding can inject "bogus” data to corrupt the content distribution
process so as to hinder the information dispersal or even
deplete the network resource. Therefore, content
verification is an important and practical issue when
network coding is employed. When random linear
network coding is used, it is infeasible for the source of
the content to sign all the data, and hence, the traditional
"hash-and-sign” methods are no longer applicable.
Recently, a new on-the-fly verification technique has
been proposed by Krohn et al. (IEEE S&P '04), which
employs a classical homomorphic hash function.
However, this technique is difficult to be applied to
network coding because of high computational and
communication overhead. We explore this issue further

by carefully analyzing different types of overhead, and
propose methods to help reducing both the computational
and communication cost, and provide provable security
at the same time.

28. Security of Bertino- Recently, Bertino, Shang and Wagstaff proposed a time- 2012
Shang-Wagstaff Time- bound hierarchical key management scheme for secure
Bound Hierarchical broadcasting. Their scheme is built on elliptic curve
Key Management cryptography and implemented with tamper-resistant
Scheme for Secure devices. In this paper, we present two collusion attacks
Broadcasting on Bertino-Shang-Wagstaff scheme. The first attack does
not need to compromise any decryption device, while the
second attack requires to compromise single decryption
device only. Both attacks are feasible and effective.
29. Survivability Radio Frequency Identification (RFID) has been 2012
Experiment and developed as an important technique for many high
Attack security and high integrity settings. In this paper, we
Characterization for study survivability issues for RFID. We first present an
RFID RFID survivability experiment to define a foundation to
measure the degree of survivability of an RFID system
under varying attacks. Then we model a series of
malicious scenarios using stochastic process algebras and
study the different effects of those attacks on the ability
of the RFID system to provide critical services even
when parts of the system have been damaged. Our
simulation model relates its statistic to the attack
strategies and security recovery. The model helps system
designers and security specialists to identify the most
devastating attacks given the attacker's capacities and the
system's recovery abilities. The goal is to improve the
system survivability given possible attacks. Our model is
the first of its kind to formally represent and simulate
attacks on RFID systems and to quantitatively measure
the degree of survivability of an RFID system under
those attacks.
30. Persuasive Cued This paper presents an integrated evaluation of the 2012
Click-Points Design, Persuasive Cued Click-Points graphical password
Implementation, and scheme, including usability and security evaluations, and
Evaluation of a implementation considerations. An important usability
Knowledge- Based goal for knowledge-based authentication systems is to
Authentication support users in selecting passwords of higher security,
Mechanism in the sense of being from an expanded effective security
space. We use persuasion to influence user choice in
click-based graphical passwords, encouraging users to
select more random, and hence more difficult to guess,
click-points.

31. Resilient Modern computer systems are built on a foundation of 2012
Authenticated software components from a variety of vendors. While
Execution of Critical critical applications may undergo extensive testing and
Applications in evaluation procedures, the heterogeneity of software
Untrusted sources threatens the integrity of the execution
Environments environment for these trusted programs. For instance, if
an attacker can combine an application exploit with a
privilege escalation vulnerability, the operating system
(OS) can become corrupted. Alternatively, a malicious or
faulty device driver running with kernel privileges could
threaten the application. While the importance of
ensuring application integrity has been studied in prior
work, proposed solutions immediately terminate the
application once corruption is detected. Although, this
approach is sufficient for some cases, it is undesirable for
many critical applications. In order to overcome this
shortcoming, we have explored techniques for leveraging
a trusted virtual machine monitor (VMM) to observe the
application and potentially repair damage that occurs. In
this paper, we describe our system design, which
leverages efficient coding and authentication schemes,
and we present the details of our prototype
implementation to quantify the overhead of our
approach. Our work shows that it is feasible to build a
resilient execution environment, even in the presence of a
corrupted OS kernel, with a reasonable amount of storage
and performance overhead.

TECHNOLOGY : JAVA

DOMAIN : IEEE TRANSACTIONS ON DATA MINING

1. A Survival Modeling In this paper, we propose a survival modeling approach 2012
Approach to
to promoting ranking diversity for biomedical
Biomedical Searchinformation retrieval. The proposed approach concerns
Result Diversification
with finding relevant documents that can deliver more
Using Wikipedia different aspects of a query. First, two probabilistic
models derived from the survival analysis theory are
proposed for measuring aspect novelty.
2. A Fuzzy Approach for In this paper, we propose a new fuzzy clustering 2012
Multitype Relational approach for multitype relational data (FC-MR). In FC-
Data Clustering MR, different types of objects are clustered
simultaneously. An object is assigned a large

membership with respect to a cluster if its related objects
in this cluster have high rankings.
3. Anonimos: An LP- We present Anonimos, a Linear Programming-based 2012
Based Approach for technique for anonymization of edge weights that
Anonymizing preserves linear properties of graphs. Such properties
Weighted Social form the foundation of many important graph-theoretic
Network Graphs algorithms such as shortest paths problem, k-nearest
neighbors, minimum cost spanning Tree and maximizing
information spread.
4. A Methodology for In this paper, we tackle discrimination prevention in data 2012
Direct and Indirect mining and propose new techniques applicable for direct
Discrimination or indirect Discrimination prevention individually or
Prevention in Data both at the same time. We discuss how to clean training
Mining datasets and outsourced datasets in such a way that direct
and/or indirect discriminatory decision rules are
converted to legitimate (non-discriminatory)
Classification rules.
5. Mining Web Graphs In this paper, aiming at providing a general framework 2012
for Recommendations on mining Web graphs for recommendations, (1) we first
propose a novel diffusion method which propagates
similarities between different nodes and generates
recommendations; (2) then we illustrate how to
generalize different recommendation problems into our
graph diffusion framework.
6. Prediction of User’s Predicting user's behavior while serving the Internet can 2012
Web-Browsing be applied effectively in various critical applications.
Behavior: Application Such application has traditional tradeoffs between
of Markov Model modeling complexity and prediction accuracy. In this
paper, we analyze and study Markov model and all- Kth
Markov model in Web prediction. We propose a new
modified Markov model to alleviate the issue of
scalability in the number of paths.
7. Prototype Selection This paper provides a survey of the prototype selection 2012
for Nearest Neighbor methods proposed in the literature from a theoretical and
Classification: empirical point of view. Considering a theoretical point
Taxonomy and of view, we propose a taxonomy based on the main
Empirical Study characteristics presented in prototype selection and we
analyze their advantages and drawbacks, the nearest
neighbor classifier suffers from several drawbacks such
as high storage requirements, low efficiency in
classification response, and low noise Tolerance.
8. Query Planning for We present a low-cost, scalable technique to answer 2012
Continuous continuous aggregation queries using a network of
Aggregation Queries aggregators of dynamic data items. In such a network of
over a Network of data aggregators, each data aggregator serves a set of
Data Aggregators data items at specific coherencies.

9. Revealing Density- In this paper, we introduce a novel density-based 2012
Based Clustering network clustering method, called gSkeletonClu (graph-
Structure from the skeleton based clustering). By projecting an undirected
Core-Connected Tree network to its core-connected maximal spanning tree, the
of a Network clustering problem can be converted to detect core
connectivity components on the tree.
10. Scalable Learning of This study of collective behavior is to understand how 2012
Collective Behavior individuals behave in a social networking environment.
Oceans of data generated by social media like Facebook,
Twitter, Flickr, and YouTube present opportunities and
challenges to study collective behavior on a large scale.
In this work, we aim to learn to predict collective
behavior in social media
11. Weakly Supervised This paper proposes a novel probabilistic modeling 2012
Joint Sentiment-Topic framework called joint sentiment-topic (JST) model
Detection from Text based on latent Dirichlet allocation (LDA), which detects
sentiment and topic simultaneously from text. A
reparameterized version of the JST model called
Reverse-JST, obtained by reversing the sequence of
sentiment and topic generation in the modeling process,
is also studied.
12. A Framework for Due to a wide range of potential applications, research on 2012
Personal Mobile mobile commerce has received a lot of interests from
Commerce Pattern both of the industry and academia. Among them, one of
Mining and Prediction the active topic areas is the mining and prediction of
users’ mobile commerce behaviors such as their
movements and purchase transactions. In this paper, we
propose a novel framework, called Mobile Commerce
Explorer (MCE), for mining and prediction of mobile
users’ movements and purchase transactions under the
context of mobile commerce. The MCE framework
consists of three major components: 1) Similarity
Inference Model (SIM) for measuring the similarities
among stores and items, which are two basic mobile
commerce entities considered in this paper; 2) Personal
Mobile Commerce Pattern Mine (PMCP-Mine)
algorithm for efficient discovery of mobile users’
Personal Mobile Commerce Patterns (PMCPs); and 3)
Mobile Commerce Behavior Predictor (MCBP) for
prediction of possible mobile user behaviors. To our best
knowledge, this is the first work that facilitates mining
and prediction of mobile users’ commerce behaviors in
order to recommend stores and items previously
unknown to a user. We perform an extensive
experimental evaluation by simulation and show that our
proposals produce excellent results.

13. Efficient Extended Extended Boolean retrieval (EBR) models were proposed 2012
Boolean Retrieval nearly three decades ago, but have had little practical
impact, despite their significant advantages compared to
either ranked keyword or pure Boolean retrieval. In
particular,EBR models produce meaningful rankings;
their query model allows the representation of complex
concepts in an and-or format; and they are scrutable, in
that the score assigned to a document depends solely on
the content of that document, unaffected by any
collection statistics or other external factors. These
characteristics make EBR models attractive in domains
typified by medical and legal searching, where the
emphasis is on iterative development of reproducible
complex queries of dozens or even hundreds of terms.
However, EBR is much more computationally expensive
than the alternatives. We consider the implementation of
the p-norm approach to EBR, and demonstrate that ideas
used in the max-score and wand exact optimization
techniques for ranked keyword retrieval can be adaptedto
allow selective bypass of documents via a low-cost
screening process for this and similar retrieval models.
We also propose term independent bounds that are able
to further reduce the number of score calculations for
short, simple queries under the extended Boolean
retrieval model. Together, these methods yield an overall
saving from 50 to 80percent of the evaluation cost on test
queries drawn from biomedical search.

14. Improving Aggregate Recommender systems are becoming increasingly
Recommendation important to individual users and businesses for
Diversity Using providingpersonalized recommendations. However,
Ranking-Based while the majority of algorithms proposed in
Techniques recommender systems literature have focused on
improving recommendation accuracy (as exemplified by
the recent Netflix Prize competition) , other important
aspects of recommendation quality, such as the diversity
of recommendations, have often been overlooked. In this
paper, we introduce and explore a number of item
ranking techniques that can generate recommendations
that have substantially higher aggregate diversity across
all users while maintaining comparable levels of
recommendation accuracy. Comprehensive empirical
evaluation consistently shows the diversity gains of the

proposed techniques using several real-world rating
datasets and different rating prediction algorithms.

15. BibPro: A Citation Dramatic increase in the number of academic 2012
Parser Based on publications has led to growing demand for efficient
Sequence Alignment organization of the resources to meet researchers' needs.
As a result, a number of network services have compiled
databases from the public resources scattered over the
Internet. However, publications by different conferences
and journals adopt different citation styles. It is an
interesting problem to accurately extract metadata from a
citation string which is formatted in one of thousands of
different styles. It has attracted a great deal of attention in
research in recent years. In this paper, based on the
notion of sequence alignment, we present a citation
parser called BibPro that extracts components of a
citation string. To demonstrate the efficacy of BibPro, we
conducted experiments on three benchmark data sets.
The results show that BibPro achieved over 90 percent
accuracy on each benchmark. Even with citations and
associated metadata retrieved from the web as training
data, our experiments show that BibPro still achieves a
reasonable performance

16. Extending Attribute Data quantity is the main issue in the small data set 2012
Information for Small problem, because usually insufficient data will not lead
Data Set Classification to a robust classification performance. How to extract
more effective information from a small data set is thus
of considerable interest. This paper proposes a new
attribute construction approach which converts the
original data attributes into a higher dimensional feature
space to extract more attribute information by a
similarity-based algorithm using the classification-
oriented fuzzy membership function. Seven data sets
with different attribute sizes are employed to examine the
performance of the proposed method. The results show
that the proposed method has a superior classification
performance when compared to principal component
analysis (PCA), kernel principal component analysis
(KPCA), and kernel independent component analysis
(KICA) with a Gaussian kernel in the support vector
machine (SVM) classifier

17. Horizontal Preparing a data set for analysis is generally the most 2012
Aggregations in SQL time consuming task in a data mining project, requiring
to Prepare Data Sets many complex SQL queries, joining tables, and

for Data Mining aggregating columns. Existing SQL aggregations have
Analysis limitations to prepare data sets because they return one
column per aggregated group. In general, a significant
manual effort is required to build data sets, where a
horizontal layout is required. We propose simple, yet
powerful, methods to generate SQL code to return
aggregated columns in a horizontal tabular layout,
returning a set of numbers instead of one number per
row. This new class of functions is called horizontal
aggregations. Horizontal aggregations build data sets
with a horizontal denormalized layout (e.g., point-
dimension, observationvariable, instance-feature), which
is the standard layout required by most data mining
algorithms. We propose three fundamental methods to
evaluate horizontal aggregations: CASE: Exploiting the
programming CASE construct; SPJ: Based on standard
relational algebra operators (SPJ queries); PIVOT: Using
the PIVOT operator, which is offered by some DBMSs.
Experiments with large tables compare the proposed
query evaluation methods. Our CASE method has similar
speed to the PIVOT operator and it is much faster than
the SPJ method. In general, the CASE and PIVOT
methods exhibit linear scalability, whereas the SPJ
method does

18. Enabling Multilevel Privacy Preserving Data Mining (PPDM) addresses the 2012
Trust in Privacy problem of developing accurate models about aggregated
Preserving Data data without access to precise information in individual
Mining data record. A widely studied perturbation-based PPDM
approach introduces random perturbation to individual
values to preserve privacy before data are published.
Previous solutions of this approach are limited in their
tacit assumption of single-level trust on data miners. In
this work, we relax this assumption and expand the scope
of perturbation-based PPDM to Multilevel Trust (MLT-
PPDM). In our setting, the more trusted a data miner is,
the less perturbed copy of the data it can access. Under
this setting, a malicious data miner may have access to
differently perturbed copies of the same data through
various means, and may combine these diverse copies to
jointly infer additional information about the original
data that the data owner does not intend to release.
Preventing such diversity attacks is the key challenge of
providing MLT-PPDM services. We address this
challenge by properly correlating perturbation across
copies at different trust levels. We prove that our solution

is robust against diversity attacks with respect to our
privacy goal. That is, for data miners who have access to
an arbitrary collection of the perturbed copies, our
solution prevent them from jointly reconstructing the
original data more accurately than the best effort using
any individual copy in the collection. Our solution allows
a data owner to generate perturbed copies of its data for
arbitrary trust levels ondemand.This feature offers data
owners maximum flexibility.
19. Using Rule Ontology Inferential rules are as essential to the Semantic Web 2012
in Repeated Rule applications as ontology. Therefore, rule acquisition is
Acquisition from also an important issue, and the Web that implies
Similar Web Sites inferential rules can be a major source of rule acquisition.
We expect that it will be easier to acquire rules from a
site by using similar rules of other sites in the same
domain rather than starting from scratch. We proposed an
automatic rule acquisition procedure using a rule
ontology RuleToOnto, which represents information
about the rule components and their structures. The rule
acquisition procedure consists of the rule component
identification step and the rule composition step. We
developed A* algorithm for the rule composition and we
performed experiments demonstrating that our ontology-
based rule acquisition approach works in a real-world
application.
20. Efficient Processing of There is a growing need for systems that react 2012
Uncertain Events in automatically to events. While some events are generated
Rule-Based Systems externally and deliver data across distributed systems,
others need to be derived by the system itself based on
available information. Event derivation is hampered by
uncertainty attributed to causes such as unreliable data
sources or the inability to determine with certainty
whether an event has actually occurred, given available
information. Two main challenges exist when designing
a solution for event derivation under uncertainty. First,
event derivation should scale under heavy loads of
incoming events. Second, the associated probabilities
must be correctly captured and represented. We present a
solution to both problems by introducing a novel generic
and formal mechanism and framework for managing
event derivation under uncertainty. We also provide
empirical evidence demonstrating the scalability and
accuracy of our approach
21. Feature Selection Data and knowledge management systems employ 2012
Based on Class- feature selection algorithms for removing irrelevant,
Dependent Densities redundant, and noisy information from the data. There

for High-Dimensional are two well-known approaches to feature selection,
Binary Data feature ranking (FR) and feature subset selection (FSS).
In this paper, we propose a new FR algorithm, termed as
class-dependent density-based feature elimination
(CDFE), for binary data sets. Our theoretical analysis
shows that CDFE computes the weights, used for feature
ranking, more efficiently as compared to the mutual
information measure. Effectively, rankings obtained from
both the two criteria approximate each other. CDFE uses
a filtrapper approach to select a final subset. For data sets
having hundreds of thousands of features, feature
selection with FR algorithms is simple and
computationally efficient but redundant information may
not be removed. On the other hand, FSS algorithms
analyze the data for redundancies but may become
computationally impractical on high-dimensional data
sets. We address these problems by combining FR and
FSS methods in the form of a two-stage feature selection
algorithm. When introduced as a preprocessing step to
the FSS algorithms, CDFE not only presents them with a
feature subset, good in terms of classification, but also
relieves them from heavy computations. Two FSS
algorithms are employed in the second stage to test the
two-stage feature selection idea. We carry out
experiments with two different classifiers (naive Bayes'
and kernel ridge regression) on three different real-life
data sets (NOVA, HIVA, and GINA) of the”Agnostic
Learning versus Prior Knowledge” challenge. As a stand-
alone method, CDFE shows up to about 92 percent
reduction in the feature set size. When combined with the
FSS algorithms in two-stages, CDFE significantly
improves their classification accuracy and exhibits up to
97 percent reduction in the feature set size. We also
compared CDFE against the winning entries of the
challenge and f- und that it outperforms the best results
on NOVA and HIVA while obtaining a third position in
case of GINA.

22. Ranking Model With the explosive emergence of vertical search 2012
Adaptation for domains, applying the broad-based ranking model
Domain-Specific directly to different domains is no longer desirable due to
Search domain differences, while building a unique ranking
model for each domain is both laborious for labeling data
and time-consuming for training models. In this paper,
we address these difficulties by proposing a
regularization based algorithm called ranking adaptation

SVM (RA-SVM), through which we can adapt an
existing ranking model to a new domain, so that the
amount of labeled data and the training cost is reduced
while the performance is still guaranteed. Our algorithm
only requires the prediction from the existing ranking
models, rather than their internal representations or the
data from auxiliary domains. In addition, we assume that
documents similar in the domain-specific feature space
should have consistent rankings, and add some
constraints to control the margin and slack variables of
RA-SVM adaptively. Finally, ranking adaptability
measurement is proposed to quantitatively estimate if an
existing ranking model can be adapted to a new domain.
Experiments performed over Letor and two large scale
datasets crawled from a commercial search engine
demonstrate the applicabilities of the proposed ranking
adaptation algorithms and the ranking adaptability
measurement.
23. Slicing: A New Several anonymization techniques, such as generalization 2012
Approach to Privacy and bucketization, have been designed for privacy
Preserving Data preserving microdata publishing. Recent work has shown
Publishing that general ization loses considerable amount of
information, especially for high-dimensional data.
Bucketization, on the other hand, does not prevent
membership disclosure and does not apply for data that
do not have a clear separation between quasi- identifying
attributes and sensitive attributes. In this paper, we
present a novel technique called slicing, which partitions
the data both horizontally and vertically. We show that
slicing preserves better data utility than generalization
and can be used for membership disclosure protection.
Another important advantage of slicing is that it can
handle high-dimensional data. We show how slicing can
be used for attribute disclosure protection and develop an
efficient algorithm for computing the sliced data that
obey the ℓ-diversity requirement. Our workload
experiments confirm that slicing preserves better utility
than generalization and is more effective than
bucketization in workloads involving the sensitive
attribute. Our experiments also demonstrate that slicing
can be used to prevent membership disclosure.
24. Improving Aggregate Recommender systems are becoming increasingly 2012
Recommendation important to individual users and businesses for
Diversity Using providing personalized recommendations. However,
Ranking-Based while the majority of algorithms proposed in
Techniques- projects recommender systems literature have focused on

improving recommendation accuracy, other important
aspects of recommendation quality, such as the diversity
of recommendations, have often been overlooked. In this
paper, we introduce and explore a number of item
ranking techniques that can generate recommendations
that have substantially higher aggregate diversity across
all users while maintaining comparable levels of
recommendation accuracy. Comprehensive empirical
evaluation consistently shows the diversity gains of the
proposed techniques using several real-world rating
datasets and different rating prediction algorithms.
to Prepare Data Sets many complex SQL queries, joining tables and
manual effort is required to
build data sets, where a horizontal layout is required. We
propose simple, yet powerful, methods to generate SQL
code to return aggregated columns in a horizontal tabular
layout, returning a set of numbers instead of one number
per row. This new class of functions is called horizontal
aggregations.
Horizontal aggregations build data sets with a horizontal
denormalized layout (e.g. point-dimension, observation-
variable, instance-feature), which is the standard layout
required by most data mining algorithms. We propose
three fundamental methods to evaluate horizontal
aggregations: CASE: Exploiting
the programming CASE construct; SPJ: Based on
standard relational algebra operators (SPJ queries);
PIVOT: Using the PIVOT operator, which is offered by
some DBMSs. Experiments with large tables compare
the proposed query evaluation methods. Our CASE
method has similar speed to the PIVOT operator and it is
much faster than the SPJ method. In general, the CASE
and PIVOT methods exhibit linear scalability,
whereasthe SPJ method does not
26. Scalable Learning of This study of collective behavior is to understand how 2012
Collective Behavior - individuals behave in a social networking environment.
projects 2012 Oceans of data generated by social media like Face book,
Twitter, Flicker, and YouTube present opportunities and
challenges to study collective behavior on a large scale.
In this work, we aim to learn to predict collective
behavior in social media. In particular, given information

about some individuals, how can we infer the behavior of
unobserved individuals in the same network? A social-
dimension-based approach has been shown effective in
addressing the heterogeneity of connections presented in
social media. However, the networks in social media are
normally of colossal size, involving hundreds of
thousands of actors. The scale of these networks entails
scalable learning of models for collective behavior
prediction. To address the scalability issue, we propose
an edge-centric clustering scheme to extract sparse social
dimensions. With sparse social dimensions, the proposed
approach can efficiently handle networks of millions of
actors while demonstrating a comparable prediction
performance to other non-scalable methods
27. Outsourced Similarity This paper considers a cloud computing setting in which 2012
Search on Metric Data similarity querying of metric data is outsourced to a
Assets – projects service provider. The data is to be revealed only to
trusted users, not to the service provider or anyone else.
Users query the server for the most similar data objects
to a query example. Outsourcing offers the data owner
scalability and a low-initial investment. The need for
privacy may be due to the data being sensitive (e.g., in
medicine), valuable (e.g., in astronomy), or otherwise
confidential. Given this setting, the paper presents
techniques that transform the data prior to supplying it to
the service provider for similarity queries on the
transformed data. Our techniques provide interesting
trade-offs between query cost and accuracy. They are
then further extended to offer an intuitive privacy
guarantee. Empirical studies with real data demonstrate
that the techniques are capable of offering privacy while
enabling efficient and accurate processing of similarity
queries.
28. A Framework for A Time Series Clique (TSC) consists of multiple time 2012
Similarity Search of series which are related to each other by natural relations.
Time Series Cliques The natural relations that are found between the time
with Natural Relations series depend on the application domains. For example, a
TSC can consist of time series which are trajectories in
video that have spatial relations. In conventional time
series retrieval, such natural relations between the time
series are not considered. In this paper, we formalize the
problem of similarity search over a TSC database. We
develop a novel framework for efficient similarity search
on TSC data. The framework addresses the following
issues. First, it provides a compact representation for
TSC data. Second, it uses a multidimensional relation

vector to capture the natural relations between the
multiple time series in a TSC. Lastly, the framework
defines a novel similarity measure that uses the compact
representation and the relation vector. We conduct an
extensive performance study, using both real-life and
synthetic data sets. From the performance study, we
show that our proposed framework is both effective and
efficient for TSC retrieval
29. A Genetic Several systems that rely on consistent data to offer high- 2012
Programming quality services, such as digital libraries and e-commerce
Approach to Record brokers, may be affected by the existence of duplicates,
Deduplication quasi replicas, or near-duplicate entries in their
repositories. Because of that, there have been significant
investments from private and government organizations
for developing methods for removing replicas from its
data repositories. This is due to the fact that clean and
replica-free repositories not only allow the retrieval of
higher quality information but also lead to more concise
data and to potential savings in computational time and
resources to process this data. In this paper, we propose a
genetic programming approach to record deduplication
that combines several different pieces of evidence
extracted from the data content to find a deduplication
function that is able to identify whether two entries in a
repository are replicas or not. As shown by our
experiments, our approach outperforms an existing state-
of-the-art method found in the literature. Moreover, the
suggested functions are computationally less demanding
since they use fewer evidence. In addition, our genetic
programming approach is capable of automatically
adapting these functions to a given fixed replica
identification boundary, freeing the user from the burden
of having to choose and tune this parameter.
30. A Probabilistic Databases enable users to precisely express their 2012
Scheme for Keyword- informational needs using structured queries. However,
Based Incremental database query construction is a laborious and error-
Query Construction prone process, which cannot be performed well by most
end users. Keyword search alleviates the usability
problem at the price of query expressiveness. As
keyword search algorithms do not differentiate between
the possible informational needs represented by a
keyword query, users may not receive adequate results.
This paper presents IQP - a novel approach to bridge the
gap between usability of keyword search and
expressiveness of database queries. IQP enables a user to
start with an arbitrary keyword query and incrementally

refine it into a structured query through an interactive
interface. The enabling techniques of IQP include: 1) a
probabilistic framework for incremental query
construction; 2) a probabilistic model to assess the
possible informational needs represented by a keyword
query; 3) an algorithm to obtain the optimal query
construction process. This paper presents the detailed
design of IQP, and demonstrates its effectiveness and
scalability through experiments over real-world data and
a user study.
31. Anónimos An LP- The increasing popularity of social networks has initiated 2012
Based Approach for a fertile research area in information extraction and data
Anonymizing mining. Anonymization of these social graphs is
Weighted Social important to facilitate publishing these data sets for
Network Graphs analysis by external entities. Prior work has concentrated
mostly on node identity anonymization and structural
anonymization. But with the growing interest in
analyzing social networks as a weighted network, edge
weight anonymization is also gaining importance. We
present Anónimos, a Linear Programming-based
technique for anonymization of edge weights that
preserves linear properties of graphs. Such properties
form the foundation of many important graph-theoretic
algorithms such as shortest paths problem, k-nearest
neighbors, minimum cost spanning tree, and maximizing
information spread. As a proof of concept, we apply
Anónimos to the shortest paths problem and its
extensions, prove the correctness, analyze complexity,
and experimentally evaluate it using real social network
data sets. Our experiments demonstrate that Anónimos
anonymizes the weights, improves k-anonymity of the
weights, and also scrambles the relative ordering of the
edges sorted by weights, thereby providing robust and
effective anonymization of the sensitive edge-weights.
We also demonstrate the composability of different
models generated using Anónimos, a property that allows
a single anonymized graph to preserve multiple linear
properties.

32. Answering General Time is an important dimension of relevance for a large 2012
Time-Sensitive number of searches, such as over blogs and news
Queries archives. So far, research on searching over such
collections has largely focused on locating topically
similar documents for a query. Unfortunately, topic
similarity alone is not always sufficient for document
ranking. In this paper, we observe that, for an important

class of queries that we call time-sensitive queries, the
publication time of the documents in a news archive is
important and should be considered in conjunction with
the topic similarity to derive the final document ranking.
Earlier work has focused on improving retrieval for
“recency” queries that target recent documents. We
propose a more general framework for handling time-
sensitive queries and we automatically identify the
important time intervals that are likely to be of interest
for a query. Then, we build scoring techniques that
seamlessly integrate the temporal aspect into the overall
ranking mechanism. We present an extensive
experimental evaluation using a variety of news article
data sets, including TREC data as well as real web data
analyzed using the Amazon Mechanical Turk. We
examine several techniques for detecting the important
time intervals for a query over a news archive and for
incorporating this information in the retrieval process.
We show that our techniques are robust and significantly
improve result quality for time-sensitive queries
compared to state-of-the-art retrieval techniques.

33. Clustering with All clustering methods have to assume some cluster 2012
Multiviewpoint-Based relationship among the data objects that they are applied
Similarity Measure on. Similarity between a pair of objects can be defined
either explicitly or implicitly. In this paper, we introduce
a novel multiviewpoint-based similarity measure and two
related clustering methods. The major difference between
a traditional dissimilarity/similarity measure and ours is
that the former uses only a single viewpoint, which is the
origin, while the latter utilizes many different viewpoints,
which are objects assumed to not be in the same cluster
with the two objects being measured. Using multiple
viewpoints, more informative assessment of similarity
could be achieved. Theoretical analysis and empirical
study are conducted to support this claim. Two criterion
functions for document clustering are proposed based on
this new measure. We compare them with several well-
known clustering algorithms that use other popular
similarity measures on various document collections to
verify the advantages of our proposal.
34. Cluster-Oriented This paper presents a novel cluster-oriented ensemble 2012
Ensemble Classifier classifier. The proposed ensemble classifier is based on
Impact of Multicluster original concepts such as learning of cluster boundaries
Characterization on by the base classifiers and mapping of cluster
Ensemble Classifier confidences to class decision using a fusion classifier.

Learning The categorized data set is characterized into multiple
clusters and fed to a number of distinctive base
classifiers. The base classifiers learn cluster boundaries
and produce cluster confidence vectors. A second level
fusion classifier combines the cluster confidences and
maps to class decisions. The proposed ensemble
classifier modifies the learning domain for the base
classifiers and facilitates efficient learning. The proposed
approach is evaluated on benchmark data sets from UCI
machine learning repository to identify the impact of
multicluster boundaries on classifier learning and
classification accuracy. The experimental results and
two-tailed sign test demonstrate the superiority of the
proposed cluster-oriented ensemble classifier over
existing ensemble classifiers published in the literature.
35. Effective Pattern Many data mining techniques have been proposed for 2012
Discovery for Text mining useful patterns in text documents. However, how
Mining to effectively use and update discovered patterns is still
an open research issue, especially in the domain of text
mining. Since most existing text mining methods adopted
term-based approaches, they all suffer from the problems
of polysemy and synonymy. Over the years, people have
often held the hypothesis that pattern (or phrase)-based
approaches should perform better than the term-based
ones, but many experiments do not support this
hypothesis. This paper presents an innovative and
effective pattern discovery technique which includes the
processes of pattern deploying and pattern evolving, to
improve the effectiveness of using and updating
discovered patterns for finding relevant and interesting
information. Substantial experiments on RCV1 data
collection and TREC topics demonstrate that the
proposed solution achieves encouraging performance.
36. Efficient Fuzzy Type- In a traditional keyword-search system over XML data, a 2012
Ahead Search in XML user composes a keyword query, submits it to the system,
Data and retrieves relevant answers. In the case where the user
has limited knowledge about the data, often the user feels
“left in the dark” when issuing queries, and has to use a
try-and-see approach for finding information. In this
paper, we study fuzzy type-ahead search in XML data, a
new information-access paradigm in which the system
searches XML data on the fly as the user types in query
keywords. It allows users to explore data as they type,
even in the presence of minor errors of their keywords.
Our proposed method has the following features: 1)
Search as you type: It extends Autocomplete by

supporting queries with multiple keywords in XML data.
2) Fuzzy: It can find high-quality answers that have
keywords matching query keywords approximately. 3)
Efficient: Our effective index structures and searching
algorithms can achieve a very high interactive speed. We
study research challenges in this new search framework.
We propose effective index structures and top-k
algorithms to achieve a high interactive speed. We
examine effective ranking functions and early
termination techniques to progressively identify the top-k
relevant answers. We have implemented our method on
real data sets, and the experimental results show that our
method achieves high search efficiency and result
quality.

37. Feature Selection Data and knowledge management systems employ 2012
Based on Class- feature selection algorithms for removing irrelevant,
Dependent Densities redundant, and noisy information from the data. There
for High-Dimensional are two well-known approaches to feature selection,
Binary Data feature ranking (FR) and feature subset selection (FSS).
In this paper, we propose a new FR algorithm, termed as
class-dependent density-based feature elimination
(CDFE), for binary data sets. Our theoretical analysis
shows that CDFE computes the weights, used for feature
ranking, more efficiently as compared to the mutual
information measure. Effectively, rankings obtained from
both the two criteria approximate each other. CDFE uses
a filtrapper approach to select a final subset. For data sets
having hundreds of thousands of features, feature
selection with FR algorithms is simple and
computationally efficient but redundant information may
not be removed. On the other hand, FSS algorithms
analyze the data for redundancies but may become
computationally impractical on high-dimensional data
sets. We address these problems by combining FR and
FSS methods in the form of a two-stage feature selection
algorithm. When introduced as a preprocessing step to
the FSS algorithms, CDFE not only presents them with a
feature subset, good in terms of classification, but also
relieves them from heavy computations. Two FSS
algorithms are employed in the second stage to test the
two-stage feature selection idea. We carry out
experiments with two different classifiers (naive Bayes'
and kernel ridge regression) on three different real-life
data sets (NOVA, HIVA, and GINA) of the”Agnostic
Learning versus Prior Knowledge” challenge. As a stand-

alone method, CDFE shows up to about 92 percent
reduction in the feature set size. When combined with the
FSS algorithms in two-stages, CDFE significantly
improves their classification accuracy and exhibits up to
97 percent reduction in the feature set size. We also
compared CDFE against the winning entries of the
challenge and f- und that it outperforms the best results
on NOVA and HIVA while obtaining a third position in
case of GINA.
38. Feedback Matching There is a need to promote drastically increased levels of 2012
Framework for interoperability of product data across a broad spectrum
Semantic of stakeholders, while ensuring that the semantics of
Interoperability of product knowledge are preserved, and when necessary,
Product Data translated. In order to achieve this, multiple methods
have been proposed to determine semantic maps across
concepts from different representations. Previous
research has focused on developing different individual
matching methods, i.e., ones that compute mapping
based on a single matching measure. These efforts
assume that some weighted combination can be used to
obtain the overall maps. We analyze the problem of
combination of multiple individual methods to determine
requirements specific to product development and
propose a solution approach called FEedback Matching
Framework with Implicit Training (FEMFIT). FEMFIT
provides the ability to combine the different matching
approaches using ranking Support Vector Machine
(ranking SVM). The method accounts for nonlinear
relations between the individual matchers. It overcomes
the need to explicitly train the algorithm before it is used,
and further reduces the decision-making load on the
domain expert by implicitly capturing the expert's
decisions without requiring him to input real numbers on
similarity. We apply FEMFIT to a subset of product
constraints across a commercial system and the ISO
standard. We observe that FEMIT demonstrates better
accuracy (average correctness of the results) and stability
(deviation from the average) in comparison with other
existing combination methods commonly assumed to be
valid in this domain.
39. Fractal-Based Intrinsic Dimensionality reduction is an important step in 2012
Dimension Estimation knowledge discovery in databases. Intrinsic dimension
and Its Application in indicates the number of variables necessary to describe a
Dimensionality data set. Two methods, box-counting dimension and
Reduction correlation dimension, are commonly used for intrinsic
dimension estimation. However, the robustness of these

two methods has not been rigorously studied. This paper
demonstrates that correlation dimension is more robust
with respect to data sample size. In addition, instead of
using a user selected distance d, we propose a new
approach to capture all log-log pairs of a data set to more
precisely estimate the correlation dimension. Systematic
experiments are conducted to study factors that influence
the computation of correlation dimension, including
sample size, the number of redundant variables, and the
portion of log-log plot used for calculation. Experiments
on real-world data sets confirm the effectiveness of
intrinsic dimension estimation with our improved
method. Furthermore, a new supervised dimensionality
reduction method based on intrinsic dimension
estimation was introduced and validated.
to Prepare Data Sets many complex SQL queries, joining tables, and
manual effort is required to build data sets, where a
horizontal layout is required. We propose simple, yet
powerful, methods to generate SQL code to return
aggregated columns in a horizontal tabular layout,
returning a set of numbers instead of one number per
row. This new class of functions is called horizontal
aggregations. Horizontal aggregations build data sets
with a horizontal denormalized layout (e.g., point-
dimension, observation-variable, instance-feature), which
is the standard layout required by most data mining
algorithms. We propose three fundamental methods to
evaluate horizontal aggregations: CASE: Exploiting the
programming CASE construct; SPJ: Based on standard
relational algebra operators (SPJ queries); PIVOT: Using
the PIVOT operator, which is offered by some DBMSs.
Experiments with large tables compare the proposed
query evaluation methods. Our CASE method has similar
speed to the PIVOT operator and it is much faster than
the SPJ method. In general, the CASE and PIVOT
methods exhibit linear scalability, whereas the SPJ
method does not.
41. Low-Rank Kernel Traditional clustering techniques are inapplicable to 2012
Matrix Factorization problems where the relationships between data points
for Large-Scale evolve over time. Not only is it important for the
Evolutionary clustering algorithm to adapt to the recent changes in the

Clustering evolving data, but it also needs to take the historical
relationship between the data points into consideration.
In this paper, we propose ECKF, a general framework for
evolutionary clustering large-scale data based on low-
rank kernel matrix factorization. To the best of our
knowledge, this is the first work that clusters large
evolutionary data sets by the amalgamation of low-rank
matrix approximation methods and matrix factorization-
based clustering. Since the low-rank approximation
provides a compact representation of the original matrix,
and especially, the near-optimal low-rank approximation
can preserve the sparsity of the original data, ECKF
gains computational efficiency and hence is applicable to
large evolutionary data sets. Moreover, matrix
factorization-based methods have been shown to
effectively cluster high-dimensional data in text mining
and multimedia data analysis. From a theoretical
standpoint, we mathematically prove the convergence
and correctness of ECKF, and provide detailed analysis
of its computational efficiency (both time and space).
Through extensive experiments performed on synthetic
and real data sets, we show that ECKF outperforms the
existing methods in evolutionary clustering.
42. Mining Online Posting reviews online has become an increasingly 2012
Reviews for Predicting popular way for people to express opinions and
Sales Performance A sentiments toward the products bought or services
Case Study in the received. Analyzing the large volume of online reviews
Movie Domain available would produce useful actionable knowledge
that could be of economic values to vendors and other
interested parties. In this paper, we conduct a case study
in the movie domain, and tackle the problem of mining
reviews for predicting product sales performance. Our
analysis shows that both the sentiments expressed in the
reviews and the quality of the reviews have a significant
impact on the future sales performance of products in
question. For the sentiment factor, we propose Sentiment
PLSA (S-PLSA), in which a review is considered as a
document generated by a number of hidden sentiment
factors, in order to capture the complex nature of
sentiments. Training an S-PLSA model enables us to
obtain a succinct summary of the sentiment information
embedded in the reviews. Based on S-PLSFA, we
propose ARSA, an Autoregressive Sentiment-Aware
model for sales prediction. We then seek to further
improve the accuracy of prediction by considering the
quality factor, with a focus on predicting the quality of a

review in the absence of user-supplied indicators, and
present ARSQA, an Autoregressive Sentiment and
Quality Aware model, to utilize sentiments and quality
for predicting product sales performance. Extensive
experiments conducted on a large movie data set confirm
the effectiveness of the proposed approach.
43. Privacy Preserving Privacy preservation is important for machine learning 2012
Decision Tree and data mining, but measures designed to protect private
Learning Using information often result in a trade-off: reduced utility of
Unrealized Data Sets the training samples. This paper introduces a privacy
preserving approach that can be applied to decision tree
learning, without concomitant loss of accuracy. It
describes an approach to the preservation of the privacy
of collected data samples in cases where information
from the sample database has been partially lost. This
approach converts the original sample data sets into a
group of unreal data sets, from which the original
samples cannot be reconstructed without the entire group
of unreal data sets. Meanwhile, an accurate decision tree
can be built directly from those unreal data sets. This
novel approach can be applied directly to the data storage
as soon as the first sample is collected. The approach is
compatible with other privacy preserving approaches,
such as cryptography, for extra protection

TECHNOLOGY : JAVA

DOMAIN : IEEE TRANSACTIONS ON MOBILE COMPUTING

1. The Boomerang We present the boomerang protocol to efficiently retain 2012
Protocol: Tying Data to information at a particular geographic location in a
Geographic Locations in sparse network of highly mobile nodes without using
Mobile Disconnected infrastructure networks. To retain information around
Networks certain physical location, each mobile device passing
that location will carry the information for a short
while.
2. Nature-Inspired Self- In this paper, we present new models and algorithms 2012
Organization, Control, for control and optimization of a class of next
and Optimization in generation communication networks: Hierarchical
Heterogeneous Wireless Heterogeneous Wireless Networks (HHWNs), under
Networks real-world physical constraints. Two biology-inspired
techniques, a Flocking Algorithm (FA) and a Particle

Swarm Optimizer (PSO), are investigated in this
context.
3. A Cost Analysis In this paper, we have developed analytical framework 2012
Framework for NEMO to measure the costs of the basic protocol for Network
Prefix Delegation-Based Mobility (NEMO), and four representative prefix
Schemes delegation-based schemes. Our results show that cost
of packet delivery through the partially optimized route
dominates over other costs.
4. OMAN: A Mobile Ad In this paper, we present a high-level view of the 2012
Hoc Network Design OMAN architecture, review specific mathematical
System models used in the network representation, and show
how OMAN is used to evaluate tradeoffs in MANET
design. Specifically, we cover three case studies of
optimization. 1-robust power control under uncertain
channel information for a single physical layer
snapshot. 2-scheduling with the availability of
directional radiation patterns. 3-optimizing topology
through movement planning of relay nodes.
5. Energy-Efficient In this paper, we formulate the resource allocation 2012
Cooperative Video problem for general multihop multicast network flows
Distribution with and derive the optimal solution that minimizes the total
Statistical QoS energy consumption while guaranteeing a statistical
Provisions over end-to-end delay bound on each network path.
Wireless Networks
6. Leveraging the In this paper, we consider the implications of spectrum 2012
Algebraic Connectivity heterogeneity on connectivity and routing in a
of a Cognitive Network Cognitive Radio Ad Hoc Network (CRAHN). We
for Routing Design study the Laplacian spectrum of the CRAHN graph
when the activity of primary users is considered. We
introduce the cognitive algebraic connectivity, i.e., the
second smallest eigenvalue of the Laplacian of a graph,
in a cognitive scenario.
7. Efficient Virtual In this paper, we will study a directional virtual 2012
Backbone Construction backbone (VB) in the network where directional
with Routing Cost antennas are used. When constructing a VB, we will
Constraint in Wireless take routing and broadcasting into account since they
Networks Using are two common operations in wireless networks.
Directional Antennas Hence, we will study a VB with guaranteed routing
costs, named ? Minimum rOuting Cost Directional VB
(?-MOC-DVB).
8. Stateless Multicast In this paper, we have developed a stateless receiver- 2012
Protocol for Ad Hoc based multicast (RBMulticast) protocol that simply
Networks. uses a list of the multicast members' (e.g., sinks')
addresses, embedded in packet headers, to enable
receivers to decide the best way to forward the
multicast traffic.

9. Detection of Selfish CCA tuning can be exploited by selfish nodes to obtain 2012
Manipulation of Carrier an unfair share of the available bandwidth.
Sensing in 802.11 Specifically, a selfish entity can manipulate the CCA
Networks threshold to ignore ongoing transmissions; this
increases the probability of accessing the medium and
provides the entity a higher, unfair share of the
bandwidth.
10. Handling Selfishness in In a mobile ad hoc network, the mobility and resource 2012
Replica Allocation over constraints of mobile nodes may lead to network
a Mobile Ad Hoc partitioning or performance degradation. Several data
Network replication techniques have been proposed to minimize
performance degradation. Most of them assume that all
mobile nodes collaborate fully in terms of sharing their
memory space. In reality, however, some nodes may
selfishly decide only to cooperate partially, or not at
all, with other nodes. These selfish nodes could then
reduce the overall data accessibility in the network. In
this paper, we examine the impact of selfish nodes in a
mobile ad hoc network from the perspective of replica
allocation. We term this selfish replica allocation. In
particular, we develop a selfish node detection
algorithm that considers partial selfishness and novel
replica allocation techniques to properly cope with
selfish replica allocation. The conducted simulations
demonstrate the proposed approach outperforms
traditional cooperative replica allocation techniques in
terms of data accessibility,
communication cost, and average query delay.
11. Acknowledgment-Based We propose a broadcast algorithm suitable for a wide 2012
Broadcast Protocol for range of vehicular scenarios, which only employs local
Reliable and Efficient information acquired via periodic beacon messages,
Data Dissemination in containing acknowledgments of the circulated
Vehicular Ad Hoc broadcast messages. Each vehicle decides whether it
Networks belongs to a connected dominating set (CDS). Vehicles
in the CDS use a shorter waiting period before possible
retransmission. At time-out expiration, a vehicle
retransmits if it is aware of at least one neighbor in
need of the message. To address intermittent
connectivity and appearance of new neighbors, the
evaluation timer can be restarted. Our algorithm
resolves propagation at road intersections without any
need to even recognize intersections. It is inherently
adaptable to different mobility regimes, without the
need to classify network or vehicle speeds. In a
thorough simulation-based performance evaluation, our
algorithm is shown to provide higher reliability and

message efficiency than existing approaches for
nonsafety applications.

12. Toward Reliable Data This paper addresses the problem of delivering data 2012
Delivery for Highly packets for highly dynamic mobile ad hoc networks in
Dynamic Mobile Ad a reliable and timely manner. Most existing ad hoc
Hoc Networks routing protocols are susceptible to node mobility,
especially for large-scale networks. Driven by this
issue, we propose an efficient Position-based
Opportunistic Routing (POR) protocol which takes
advantage of the stateless property of geographic
routing and the broadcast nature of wireless medium.
When a data packet is sent out, some of the neighbor
nodes that have overheard the transmission will serve
as forwarding candidates, and take turn to forward the
packet if it is not relayed by the specific best forwarder
within a certain period of time. By utilizing such in-
the-air backup, communication is maintained without
being interrupted. The additional latency incurred by
local route recovery is greatly reduced and the
duplicate relaying caused by packet reroute is also
decreased. In the case of communication hole, a Virtual
Destination-based Void Handling (VDVH) scheme is
further proposed to work together with POR. Both
theoretical analysis and simulation results show that
POR achieves excellent performance even under high
node mobility with acceptable overhead and the new
void handling scheme also works well.
13. Protecting Location While many protocols for sensor network security 2012
Privacy in Sensor provide confidentiality for the content of messages,
Networks against a contextual information usually remains exposed. Such
Global Eavesdropper contextual information can be exploited by an
adversary to derive sensitive information such as the
locations of monitored objects and data sinks in the
field. Attacks on these components can significantly
undermine any network application. Existing
techniques defend the leakage of location information
from a limited adversary who can only observe
network traffic in a small region. However, a stronger
adversary, the global eavesdropper, is realistic and can
defeat these existing techniques. This paper first
formalizes the location privacy issues in sensor
networks under this strong adversary model and
computes a lower bound on the communication
overhead needed for achieving a given level of location
privacy. The paper then proposes two techniques to

provide location privacy to monitored objects (source-
location privacy)—periodic collection and source
simulation—and two techniques to provide location
privacy to data sinks (sink-location privacy)—sink
simulation and backbone flooding. These techniques
provide trade-offs between privacy, communication
cost, and latency. Through analysis and simulation, we
demonstrate that the proposed techniques are efficient
and effective for source and sink-location privacy in
sensor networks.

14. local broadcastThere are two main approaches, static and dynamic, to 2012
algorithms in wireless broadcast algorithms in wireless ad hoc networks. In
ad hoc networks the static approach, local algorithms determine the
reducing the number of status (forwarding/nonforwarding) of each node
transmissions proactively based on local topology information and a
globally known priority function. In this paper, we first
show that local broadcast algorithms based on the static
approach cannot achieve a good approximation factor
to the optimum solution (an NP-hard problem).
However, we show that a constant approximation
factor is achievable if (relative) position information is
available. In the dynamic approach, local algorithms
determine the status of each node “on-the-fly” based on
local topology information and broadcast state
information. Using the dynamic approach, it was
recently shown that local broadcast algorithms can
achieve a constant approximation factor to the
optimum solution when (approximate) position
information is available. However, using position
information can simplify the problem. Also, in some
applications it may not be practical to have position
information. Therefore, we wish to know whether local
broadcast algorithms based on the dynamic approach
can achieve a constant approximation factor without
using position information. We answer this question in
the positive – we design a local broadcast algorithm in
which the status of each node is decided “on-the-fly”
and prove that the algorithm can achieve both full
delivery and a constant approximation to the optimum
solution
15. Compressed-Sensing- This article presents the design of a networked system 2012
Enabled Video for joint compression, rate control and error correction
Streaming for Wireless of video over resource-constrained embedded devices
Multimedia Sensor based on the theory of compressed sensing. The

Networks objective of this work is to design a cross-layer system
that jointly controls the video encoding rate, the
transmission rate, and the channel coding rate to
maximize the received video quality. First, compressed
sensing based video encoding for transmission over
wireless multimedia sensor networks (WMSNs) is
studied. It is shown that compressed sensing can
overcome many of the current problems of video over
WMSNs, primarily encoder complexity and low
resiliency to channel errors. A rate controller is then
developed with the objective of maintaining fairness
among video streams while maximizing the received
video quality. It is shown that the rate of compressed
sensed video can be predictably controlled by varying
only the compressed sensing sampling rate. It is then
shown that the developed rate controller can be
interpreted as the iterative solution to a convex
optimization problem representing the optimization of
the rate allocation across the network. The error
resiliency properties of compressed sensed images and
videos are then studied, and an optimal error detection
and correction scheme is presented for video
transmission over lossy channels. Finally, the entire
system is evaluated through simulation and testbed
evaluation. The rate controller is shown to outperform
existing TCP-friendly rate control schemes in terms of
both fairness and received video quality. Testbed
results also show that the rates converge to stable
values in real channels.
16. Hop-by-Hop Routing in Wireless Mesh Network (WMN) has become an 2012
Wireless Mesh important edge network to provide Internet access to
Networks with remote areas and wireless connections in a
Bandwidth Guarantees metropolitan scale. In this paper, we study the problem
of identifying the maximum available bandwidth path,
a fundamental issue in supporting quality-of-service in
WMNs. Due to interference among links, bandwidth, a
well-known bottleneck metric in wired networks, is
neither concave nor additive in wireless networks. We
propose a new path weight which captures the available
path bandwidth information. We formally prove that
our hop-by-hop routing protocol based on the new path
weight satisfies the consistency and loop-freeness
requirements. The consistency property guarantees that
each node makes a proper packet forwarding decision,
so that a data packet does traverse over the intended
path. Our extensive simulation experiments also show

that our proposed path weight outperforms existing
path metrics in identifying high-throughput paths
Network- Mobile replication techniques have been proposed to minimize
Computing, projects performance degradation. Most of them assume that all
2012 mobile nodes collaborate fully in terms of sharing their
terms of data accessibility, communication cost, and
average query delay.
18. Toward Reliable Data This paper addresses the problem of delivering data 2012
Delivery for Highly packets for highly dynamic mobile ad hoc networks in
Dynamic Mobile Ad a reliable and timely manner. Most existing ad hoc
Hoc Networks- Mobile routing protocols are susceptible to node mobility,
Computing, projects especially for large-scale networks. Driven by this
2012 issue, we propose an efficient Position-based
Opportunistic Routing (POR) protocol which takes
advantage of the stateless property of geographic
routing and the broadcast nature of wireless medium.
When a data packet is sent out, some of the neighbor
nodes that have overheard the transmission will serve
as forwarding candidates, and take turn to forward the
packet if it is not relayed by the specific best forwarder
within a certain period of time. By utilizing such in-
the-air backup, communication is maintained without
being interrupted. The additional latency incurred by
local route recovery is greatly reduced and the
duplicate relaying caused by packet reroute is also
decreased. In the case of communication hole, a Virtual
Destination-based Void Handling (VDVH) scheme is
further proposed to work together with POR. Both
theoretical analysis and simulation results show that
POR achieves excellent performance even under high

node mobility with acceptable overhead and the new
void handling scheme also works well
19. Fast Data Collection in We investigate the following fundamental question – 2012
Tree-Based Wireless how fast can information be collected from a wireless
Sensor Networks- sensor network organized as tree? To address this, we
Mobile Computing, explore and evaluate a number of different techniques
projects 2012 using realistic simulation models under the many-to-
one communication paradigm known as convergecast.
We first consider time scheduling on a single frequency
channel with the aim of minimizing the number of time
slots required (schedule length) to complete a
convergecast. Next, we combine scheduling with
transmission power control to mitigate the effects of
interference, and show that while power control helps
in reducing the schedule length under a single
frequency, scheduling transmissions using multiple
frequencies is more efficient. We give lower bounds on
the schedule length when interference is completely
eliminated, and propose algorithms that achieve these
bounds. We also evaluate the performance of various
channel assignment methods and find empirically that
for moderate size networks of about 100 nodes, the use
of multi-frequency scheduling can suffice to eliminate
most of the interference. Then, the data collection rate
no longer remains limited by interference but by the
topology of the routing tree. To this end, we construct
degree-constrained spanning trees and capacitated
minimal spanning trees, and show significant
improvement in scheduling performance over different
deployment densities. Lastly, we evaluate the impact of
different interference and channel models on the
schedule length.
20. Protecting Location The location privacy issue in sensor networks under 2012
Privacy in Sensor this strong adversary model is considered. Proposed
Networks Against a two techniques to provide location privacy to
Global Eavesdropper monitored objects (source-location privacy)-periodic
JAVA collection and source simulation-and two techniques to
provide location privacy to data sinks (sink-location
privacy)-sink simulation and backbone flooding.
21. Energy-Efficient For real-time video broadcast where multiple users are 2012
Cooperative Video interested in the same content, mobile-to-mobile
Distribution with cooperation can be utilized to improve delivery
Statistical QoS efficiency and reduce network utilization. Under such
Provisions over cooperation, however, real-time video transmission
Wireless Networks – requires end-to-end delay bounds. Due to the inherently
projects 2012 stochastic nature of wireless fading channels,

deterministic delay bounds are prohibitively difficult to
guarantee. For a scalable video structure, an alternative
is to provide statistical guarantees using the concept of
effective capacity/bandwidth by deriving quality of
service exponents for each video layer. Using this
concept, we formulate the resource allocation problem
for general multihop multicast network flows and
derive the optimal solution that minimizes the total
energy consumption while guaranteeing a statistical
end-to-end delay bound on each network path. A
method is described to compute the optimal resource
allocation at each node in a distributed fashion.
Furthermore, we propose low complexity
approximation algorithms for energy-efficient flow
selection from the set of directed acyclic graphs
forming the candidate network flows. The flow
selection and resource allocation process is adapted for
each video frame according to the channel conditions
on the network links. Considering different network
topologies, results demonstrate that the proposed
resource allocation and flow selection algorithms
provide notable performance gains with small
optimality gaps at a low computational cost.

22. A Novel MAC Scheme This paper proposes a novel medium access control 2012
for Multichannel (MAC) scheme for multichannel cognitive radio (CR)
Cognitive Radio Ad Hoc ad hoc networks, which achieves high throughput of
Networks CR system while protecting primary users (PUs)
effectively. In designing the MAC scheme, we consider
that the PU signal may cover only a part of the network
and the nodes can have the different sensing result for
the same PU even on the same channel. By allowing
the nodes to use the channel on which the PU exists as
long as their transmissions do not disturb the PU, the
proposed MAC scheme fully utilizes the spectrum
access opportunity. To mitigate the hidden PU problem
inherent to multichannel CR networks where the PU
signal is detectable only to some nodes, the proposed
MAC scheme adjusts the sensing priorities of channels
at each node with the PU detection information of other
nodes and also limits the transmission power of a CR
node to the maximum allowable power for
guaranteeing the quality of service requirement of PU.
The performance of the proposed MAC scheme is
evaluated by using simulation. The simulation results
show that the CR system with the proposed MAC

accomplishes good performance in throughput and
packet delay, while protecting PUs properly
23. A Statistical Mechanics- Characterizing the performance of ad hoc networks is 2012
Based Framework to one of the most intricate open challenges; conventional
Analyze Ad Hoc ideas based on information-theoretic techniques and
Networks with Random inequalities have not yet been able to successfully
Access tackle this problem in its generality. Motivated thus, we
promote the totally asymmetric simple exclusion
process (TASEP), a particle flow model in statistical
mechanics, as a useful analytical tool to study ad hoc
networks with random access. Employing the TASEP
framework, we first investigate the average end-to-end
delay and throughput performance of a linear multihop
flow of packets. Additionally, we analytically derive
the distribution of delays incurred by packets at each
node, as well as the joint distributions of the delays
across adjacent hops along the flow. We then consider
more complex wireless network models comprising
intersecting flows, and propose the partial mean-field
approximation (PMFA), a method that helps tightly
approximate the throughput performance of the system.
We finally demonstrate via a simple example that the
PMFA procedure is quite general in that it may be used
to accurately evaluate the performance of ad hoc
networks with arbitrary topologies.

24. Acknowledgment-Based We propose a broadcast algorithm suitable for a wide 2012
Broadcast Protocol for range of vehicular scenarios, which only employs local
Reliable and Efficient information acquired via periodic beacon messages,
Data Dissemination in containing acknowledgments of the circulated
Vehicular Ad Hoc broadcast messages. Each vehicle decides whether it
Networks belongs to a connected dominating set (CDS). Vehicles
in the CDS use a shorter waiting period before possible
retransmission. At time-out expiration, a vehicle
retransmits if it is aware of at least one neighbor in
need of the message. To address intermittent
connectivity and appearance of new neighbors, the
evaluation timer can be restarted. Our algorithm
resolves propagation at road intersections without any
need to even recognize intersections. It is inherently
adaptable to different mobility regimes, without the
need to classify network or vehicle speeds. In a
thorough simulation-based performance evaluation, our
algorithm is shown to provide higher reliability and
message efficiency than existing approaches for
nonsafety applications.

25. Characterizing the
Cellular text messaging services are increasingly being 2012
Security Implications of
relied upon to disseminate critical information during
Third-Party Emergencyemergencies. Accordingly, a wide range of
Alert Systems over organizations including colleges and universities now
Cellular Text Messaging
partner with third-party providers that promise to
Services improve physical security by rapidly delivering such
messages. Unfortunately, these products do not work as
advertised due to limitations of cellular infrastructure
and therefore provide a false sense of security to their
users. In this paper, we perform the first extensive
investigation and characterization of the limitations of
an Emergency Alert System (EAS) using text messages
as a security incident response mechanism. We show
emergency alert systems built on text messaging not
only can meet the 10 minute delivery requirement
mandated by the WARN Act, but also potentially cause
other voice and SMS traffic to be blocked at rates
upward of 80 percent. We then show that our results
are representative of reality by comparing them to a
number of documented but not previously understood
failures. Finally, we analyze a targeted messaging
mechanism as a means of efficiently using currently
deployed infrastructure and third-party EAS. In so
doing, we demonstrate that this increasingly deployed
security infrastructure does not achieve its stated
requirements for large populations.
26. Converge Cast On the In this paper, we define an ad hoc network where 2012
Capacity and Delay multiple sources transmit packets to one destination as
Tradeoffs Converge-Cast network. We will study the capacity
delay tradeoffs assuming that n wireless nodes are
deployed in a unit square. For each session (the session
is a dataflow from k different source nodes to 1
destination node), k nodes are randomly selected as
active sources and each transmits one packet to a
particular destination node, which is also randomly
selected. We first consider the stationary case, where
capacity is mainly discussed and delay is entirely
dependent on the average number of hops. We find that
the per-node capacity is Θ (1/√(n log n)) (given
nonnegative functions f(n) and g(n): f(n) = O(g(n))
means there exist positive constants c and m such that
f(n) ≤ cg(n) for all n ≥ m; f(n)= Ω (g(n)) means there
exist positive constants c and m such that f(n) ≥ cg(n)
for all n ≥ m; f(n) = Θ (g(n)) means that both f(n) = Ω
(g(n)) and f(n) = O(g(n)) hold), which is the same as
that of unicast, presented in (Gupta and Kumar, 2000).

Then, node mobility is introduced to increase network
capacity, for which our study is performed in two steps.
The first step is to establish the delay in single-session
transmission. We find that the delay is Θ (n log k)
under 1-hop strategy, and Θ (n log k/m) under 2-hop
redundant strategy, where m denotes the number of
replicas for each packet. The second step is to find
delay and capacity in multisession transmission. We
reveal that the per-node capacity and delay for 2-hop
nonredundancy strategy are Θ (1) and Θ (n log k),
respectively. The optimal delay is Θ (√(n log k)+k)
with redundancy, corresponding to a capacity of Θ
(√((1/n log k) + (k/n log k)). Therefore, we obtain that
the capacity delay tradeoff satisfies delay/rate ≥ Θ (n
log k) for both strategies.

27. Cooperative Download We consider a complex (i.e., nonlinear) road scenario 2012
in Vehicular where users aboard vehicles equipped with
Environments communication interfaces are interested in
downloading large files from road-side Access Points
(APs). We investigate the possibility of exploiting
opportunistic encounters among mobile nodes so to
augment the transfer rate experienced by vehicular
downloaders. To that end, we devise solutions for the
selection of carriers and data chunks at the APs, and
evaluate them in real-world road topologies, under
different AP deployment strategies. Through extensive
simulations, we show that carry&forward transfers can
significantly increase the download rate of vehicular
users in urban/suburban environments, and that such a
result holds throughout diverse mobility scenarios, AP
placements and network loads
28. Detection of Selfish Recently, tuning the clear channel assessment (CCA) 2012
Manipulation of Carrier threshold in conjunction with power control has been
Sensing in 802.11 considered for improving the performance of WLANs.
Networks However, we show that, CCA tuning can be exploited
by selfish nodes to obtain an unfair share of the
available bandwidth. Specifically, a selfish entity can
manipulate the CCA threshold to ignore ongoing
transmissions; this increases the probability of
accessing the medium and provides the entity a higher,
unfair share of the bandwidth. We experiment on our
802.11 testbed to characterize the effects of CCA
tuning on both isolated links and in 802.11 WLAN
configurations. We focus on AP-client(s)

configurations, proposing a novel approach to detect
this misbehavior. A misbehaving client is unlikely to
recognize low power receptions as legitimate packets;
by intelligently sending low power probe messages, an
AP can efficiently detect a misbehaving node. Our key
contributions are: 1) We are the first to quantify the
impact of selfish CCA tuning via extensive
experimentation on various 802.11 configurations. 2)
We propose a lightweight scheme for detecting selfish
nodes that inappropriately increase their CCAs. 3) We
extensively evaluate our system on our testbed; its
accuracy is 95 percent while the false positive rate is
less than 5 percent.S
29. Distributed Throughput We consider throughput-optimal power allocation in 2012
Maximization in multi-hop wireless networks. The study of this problem
Wireless Networks via has been limited due to the non-convexity of the
Random Power underlying optimization problems, that prohibits an
Allocation efficient solution even in a centralized setting. We take
a randomization approach to deal with this difficulty.
To this end, we generalize the randomization
framework originally proposed for input queued
switches to an SINR rate-based interference model.
Further, we develop distributed power allocation and
comparison algorithms that satisfy these conditions,
thereby achieving (nearly) 100% throughput. We
illustrate the performance of our proposed power
allocation solution through numerical investigation and
present several extensions for the considered problem.
30. Efficient Rendezvous Recent research shows that significant energy saving 2012
Algorithms for can be achieved in mobility-enabled wireless sensor
Mobility-Enabled networks (WSNs) that visit sensor nodes and collect
Wireless Sensor data from them via short-range communications.
Networks However, a major performance bottleneck of such
WSNs is the significantly increased latency in data
collection due to the low movement speed of mobile
base stations. To address this issue, we propose a
rendezvous-based data collection approach in which a
subset of nodes serve as rendezvous points that buffer
and aggregate data originated from sources and transfer
to the base station when it arrives. This approach
combines the advantages of controlled mobility and in-
network data caching and can achieve a desirable
balance between network energy saving and data
collection delay. We propose efficient rendezvous
design algorithms with provable performance bounds
for mobile base stations with variable and fixed tracks,

respectively. The effectiveness of our approach is
validated through both theoretical analysis and
extensive simulations.
31. Efficient Virtual Directional antennas can divide the transmission range 2012
Backbone Construction into several sectors. Thus, through switching off
with Routing Cost sectors in unnecessary directions in wireless networks,
Constraint in Wireless we can save bandwidth and energy consumption. In
Networks Using this paper, we will study a directional virtual backbone
Directional Antennas (VB) in the network where directional antennas are
used. When constructing a VB, we will take routing
and broadcasting into account since they are two
common operations in wireless networks. Hence, we
will study a VB with guaranteed routing costs, named α
Minimum rOuting Cost Directional VB (α-MOC-
DVB). Besides the properties of regular VBs, α-MOC-
DVB also has a special constraint - for any pair of
nodes, there exists at least one path all intermediate
directions on which must belong to α-MOC-DVB and
the number of intermediate directions on the path is
smaller than α times that on the shortest path. We prove
that construction of a minimum α-MOC-DVB is an
NP-hard problem in a general directed graph. A
heuristic algorithm is proposed and theoretical analysis
is also discussed in the paper. Extensive simulations
demonstrate that our α-MOC-DVB is much more
efficient in the sense of VB size and routing costs
compared to other VBs.
32. Energy-Efficient Distributed Information SHaring (DISH) is a new 2012
Strategies for cooperative approach to designing multichannel MAC
Cooperative protocols. It aids nodes in their decision making
Multichannel MAC processes by compensating for their missing
Protocols information via information sharing through
neighboring nodes. This approach was recently shown
to significantly boost the throughput of multichannel
MAC protocols. However, a critical issue for ad hoc
communication devices, viz. energy efficiency, has yet
to be addressed. In this paper, we address this issue by
developing simple solutions that reduce the energy
consumption without compromising the throughput
performance and meanwhile maximize cost efficiency.
We propose two energy-efficient strategies: in-situ
energy conscious DISH, which uses existing nodes
only, and altruistic DISH, which requires additional
nodes called altruists. We compare five protocols with
respect to these strategies and identify altruistic DISH
to be the right choice in general: it 1) conserves 40-80

percent of energy, 2) maintains the throughput
advantage, and 3) more than doubles the cost efficiency
compared to protocols without this strategy. On the
other hand, our study also shows that in-situ energy
conscious DISH is suitable only in certain limited
scenarios.
33. Estimating Parameters We propose a method for estimating parameters of 2012
of Multiple multiple target objects by using networked binary
Heterogeneous Target sensors whose locations are unknown. These target
Objects Using objects may have different parameters, such as size and
Composite Sensor perimeter length. Each sensors, which is incapable of
Nodes monitoring the target object's parameters, sends only
binary data describing whether or not it detects target
objects coming into, moving around, or leaving the
sensing area at every moment. We previously
developed a parameter estimation method for a single
target object. However, a straight-forward extension of
this method is not applicable for estimating multiple
heterogeneous target objects. This is because a
networked binary sensor at an unknown location
cannot provide information that distinguishes
individual target objects, but it can provide information
on the total perimeter length and size of multiple target
objects. Therefore, we propose composite sensor nodes
with multiple sensors in a predetermined layout for
obtaining additional information for estimating the
parameter of each target object. As an example of a
composite sensor node, we consider a two-sensor
composite sensor node, which consists of two sensors,
one at each of the two end points of a line segment of
known length. For the two-sensor composite sensor
node, measures are derived such as the two sensors
detecting target objects. These derived measures are the
basis for identifying the shape of each target object
among a given set of categories (for example, disks and
rectangles) and estimating parameters such as the
radius and lengths of two sides of each target object.
Numerical examples demonstrate that networked
composite sensor nodes consisting of two binary
sensors enable us to estimate the parameters of target
objects.

34. Fast Capture— The technology of Radio Frequency IDentification 2012
Recapture Approach for (RFID) enables many applications that rely on passive,
Mitigating the Problem battery-less wireless devices. If a RFID reader needs to
of Missing RFID Tags gather the ID from multiple tags in its range, then it

needs to run an anticollision protocol. Due to errors on
the wireless link, a single reader session, which
contains one full execution of the anticollision
protocol, may not be sufficient to retrieve the ID of all
tags. This problem can be mitigated by running
multiple, redundant reader sessions and use the
statistical relationship between these sessions. On the
other hand, each session is time consuming and
therefore the number of sessions should be kept
minimal. We optimize the process of running multiple
reader sessions, by allowing only some of the tags
already discovered to reply in subsequent reader
sessions. The estimation procedure is integrated with
an actual tree-based anticollision protocol, and
numerical results show that the reliable tag resolution
algorithm attain high speed of protocol execution,
while not sacrificing the reliability of the estimators
used to assess the probability of missing tags.
35. Fast Data Collection in We investigate the following fundamental question- 2012
Tree-Based Wireless how fast can information be collected from a wireless
Sensor Networks sensor network organized as tree? To address this, we
explore and evaluate a number of different techniques
using realistic simulation models under the many-to-
one communication paradigm known as convergecast.
We first consider time scheduling on a single frequency
channel with the aim of minimizing the number of time
slots required (schedule length) to complete a
convergecast. Next, we combine scheduling with
transmission power control to mitigate the effects of
interference, and show that while power control helps
in reducing the schedule length under a single
frequency, scheduling transmissions using multiple
frequencies is more efficient. We give lower bounds on
the schedule length when interference is completely
eliminated, and propose algorithms that achieve these
bounds. We also evaluate the performance of various
channel assignment methods and find empirically that
for moderate size networks of about 100 nodes, the use
of multifrequency scheduling can suffice to eliminate
most of the interference. Then, the data collection rate
no longer remains limited by interference but by the
topology of the routing tree. To this end, we construct
degree-constrained spanning trees and capacitated
minimal spanning trees, and show significant
improvement in scheduling performance over different
deployment densities. Lastly, we evaluate the impact of

different interference and channel models on the
schedule length.
36. Fault Localization Using Faulty components in a network need to be localized 2012
Passive End-to-End and repaired to sustain the health of the network. In this
Measurements and paper, we propose a novel approach that carefully
Sequential Testing for combines active and passive measurements to localize
Wireless Sensor faults in wireless sensor networks. More specifically,
Networks we formulate a problem of optimal sequential testing
guided by end-to-end data. This problem determines an
optimal testing sequence of network components based
on end-to-end data in sensor networks to minimize
expected testing cost. We prove that this problem is
NP-hard, and propose a recursive approach to solve it.
This approach leads to a polynomial-time optimal
algorithm for line topologies while requiring
exponential running time for general topologies. We
further develop two polynomial-time heuristic schemes
that are applicable to general topologies. Extensive
simulation shows that our heuristic schemes only
require testing a very small set of network components
to localize and repair all faults in the network. Our
approach is superior to using active and passive
measurements in isolation. It also outperforms the
state-of-the-art approaches that localize and repair all
faults in a network.
37. FESCIM Fair, Efficient, In multihop cellular networks, the mobile nodes usually 2012
and Secure Cooperation relay others' packets for enhancing the network
Incentive Mechanism performance and deployment. However, selfish nodes
for Multihop Cellular usually do not cooperate but make use of the
Networks cooperative nodes to relay their packets, which has a
negative effect on the network fairness and
performance. In this paper, we propose a fair and
efficient incentive mechanism to stimulate the node
cooperation. Our mechanism applies a fair charging
policy by charging the source and destination nodes
when both of them benefit from the communication. To
implement this charging policy efficiently, hashing
operations are used in the ACK packets to reduce the
number of public-key-cryptography operations.
Moreover, reducing the overhead of the payment
checks is essential for the efficient implementation of
the incentive mechanism due to the large number of
payment transactions. Instead of generating a check per
message, a small-size check can be generated per route,
and a check submission scheme is proposed to reduce
the number of submitted checks and protect against

collusion attacks. Extensive analysis and simulations
demonstrate that our mechanism can secure the
payment and significantly reduce the checks' overhead,
and the fair charging policy can be implemented almost
computationally free by using hashing operations.
38. Geometry and Motion- This paper presents positioning algorithms for cellular 2012
Based Positioning network-based vehicle tracking in severe non-line-of-
Algorithms for Mobile sight (NLOS) propagation scenarios. The aim of the
Tracking in NLOS algorithms is to enhance positional accuracy of
Environments network-based positioning systems when the GPS
receiver does not perform well due to the complex
propagation environment. A one-step position
estimation method and another two-step method are
proposed and developed. Constrained optimization is
utilized to minimize the cost function which takes
account of the NLOS error so that the NLOS effect is
significantly reduced. Vehicle velocity and heading
direction measurements are exploited in the algorithm
development, which may be obtained using a
speedometer and a heading sensor, respectively. The
developed algorithms are practical so that they are
suitable for implementation in practice for vehicle
applications. It is observed through simulation that in
severe NLOS propagation scenarios, the proposed
positioning methods outperform the existing cellular
network-based positioning algorithms significantly.
Further, when the distance measurement error is
modeled as the sum of an exponential bias variable and
a Gaussian noise variable, the exact expressions of the
CRLB are derived to benchmark the performance of
the positioning algorithms.
Network replication techniques have been proposed to minimize
performance degradation. Most of them assume that all
mobile nodes collaborate fully in terms of sharing their

terms of data accessibility, communication cost, and
average query delay.
40. Heuristic Burst IEEE 802.16 OFDMA systems have gained much 2012
Construction Algorithm attention for their ability to support high transmission
for Improving Downlink rates and broadband access services. For multiuser
Capacity in IEEE environments, IEEE 802.16 OFDMA systems require a
802.16 OFDMA resource allocation algorithm to use the limited
Systems downlink resource efficiently. The IEEE 802.16
standard defines that resource allocation should be
performed with a rectangle region of slots, called a
burst. However, the standard does not specify how to
construct bursts. In this paper, we propose a heuristic
burst construction algorithm, called HuB, to improve
the downlink capacity in IEEE 802.16 OFDMA
systems. To increase the downlink capacity, during
burst constructions HuB reduces resource wastage by
considering padded slots and unused slots and reduces
resource usage by considering the power boosting
possibility. For simple burst constructions, HuB makes
a HuB-tree, in which a node represents an available
downlink resource and edges of a node represent a
burst rectangle region. Thus, making child nodes of a
parent node is the same as constructing a burst in a
given downlink resource. We analyzed the proposed
algorithm and performed simulations to compare the
performance of the proposed algorithm with existing
algorithms. Our simulation study results show that HuB
shows improved downlink capacity over existing
algorithms.
41. Hop-by-Hop Routing in Wireless Mesh Network (WMN) has become an 2012
Wireless Mesh important edge network to provide Internet access to
Networks with remote areas and wireless connections in a
Bandwidth Guarantees metropolitan scale. In this paper, we study the problem
of identifying the maximum available bandwidth path,
a fundamental issue in supporting quality-of-service in
WMNs. Due to interference among links, bandwidth, a
well-known bottleneck metric in wired networks, is
neither concave nor additive in wireless networks. We
propose a new path weight which captures the available
path bandwidth information. We formally prove that
our hop-by-hop routing protocol based on the new path
weight satisfies the consistency and loop-freeness

requirements. The consistency property guarantees that
each node makes a proper packet forwarding decision,
so that a data packet does traverse over the intended
path. Our extensive simulation experiments also show
that our proposed path weight outperforms existing
path metrics in identifying high-throughput paths.
42. Jointly Optimal Source- Emerging media overlay networks for wireless 2012
Flow, Transmit-Power, applications aim at delivering Variable Bit Rate (VBR)
and Sending-Rate encoded media contents to nomadic end users by
Control for Maximum- exploiting the (fading-impaired and time-varying)
Throughput Delivery of access capacity offered by the "last-hop” wireless
VBR Traffic over Faded channel. In this application scenario, a still open
Links question concerns the closed-form design of control
policies that maximize the average throughput sent
over the wireless last hop, under constraints on the
maximum connection bandwidth available at the
Application (APP) layer, the queue capacity available
at the Data Link (DL) layer, and the average and peak
energies sustained by the Physical (PHY) layer. The
approach we follow relies on the maximization on a
per-slot basis of the throughput averaged over the
fading statistic and conditioned on the queue state,
without resorting to cumbersome iterative algorithms.
The resulting optimal controller operates in a cross-
layer fashion that involves the APP, DL, and PHY
layers of the underlying protocol stack. Finally, we
develop the operating conditions allowing the proposed
controller also to maximize the unconditional average
throughput (i.e., the throughput averaged over both
queue and channel-state statistics). The carried out
numerical tests give insight into the connection
bandwidth-versus-queue delay trade-off achieved by
the optimal controller.
43. Moderated Group This paper describes the design and implementation of 2012
Authoring System for a file system-based distributed authoring system for
Campus-Wide campus-wide workgroups. We focus on documents for
Workgroups which changes by different group members are harder
to automatically reconcile into a single version. Prior
approaches relied on using group-aware editors. Others
built collaborative middleware that allowed the group
members to use traditional authoring tools. These
approaches relied on an ability to automatically detect
conflicting updates. They also operated on specific
document types. Instead, our system relies on users to
moderate and reconcile updates by other group
members. Our file system-based approach also allows

group members to modify any document type. We
maintain one updateable copy of the shared content on
each group member's node. We also hoard read-only
copies of each of these updateable copies in any
interested group member's node. All these copies are
propagated to other group members at a rate that is
solely dictated by the wireless user availability. The
various copies are reconciled using the moderation
operation; each group member manually incorporates
updates from all the other group members into their
own copy. The various document versions eventually
converge into a single version through successive
moderation operations. The system assists with this
convergence process by using the made-with
knowledge of all causal file system reads of contents
from other replicas. An analysis using a long-term
wireless user availability traces from a university
shows the strength of our asynchronous and distributed
update propagation mechanism. Our user space file
system prototype exhibits acceptable file system
performance. A subjective evaluation showed that the
moderation operation was intuitive for students.

44. Network Connectivity We investigate the communication range of the nodes 2012
with a Family of Group necessary for network connectivity, which we call
Mobility Models bidirectional connectivity, in a simple setting. Unlike in
most of existing studies, however, the locations or
mobilities of the nodes may be correlated through
group mobility: nodes are broken into groups, with
each group comprising the same number of nodes, and
lie on a unit circle. The locations of the nodes in the
same group are not mutually independent, but are
instead conditionally independent given the location of
the group. We examine the distribution of the smallest
communication range needed for bidirectional
connectivity, called the critical transmission range
(CTR), when both the number of groups and the
number of nodes in a group are large. We first
demonstrate that the CTR exhibits a parametric
sensitivity with respect to the space each group
occupies on the unit circle. Then, we offer an
explanation for the observed sensitivity by identifying
what is known as a very strong threshold and
asymptotic bounds for CTR.
45. OMAN A Mobile Ad We present a software library that aids in the design of 2012
Hoc Network Design mobile ad hoc networks (MANET). The OMAN design

System engine works by taking a specification of network
requirements and objectives, and allocates resources
which satisfy the input constraints and maximize the
communication performance objective. The tool is used
to explore networking design options and challenges,
including: power control, adaptive modulation, flow
control, scheduling, mobility, uncertainty in channel
models, and cross-layer design. The unaddressed niche
which OMAN seeks to fill is the general framework for
optimization of any network resource, under arbitrary
constraints, and with any selection of multiple
objectives. While simulation is an important part of
measuring the effectiveness of implemented
optimization techniques, the novelty and focus of
OMAN is on proposing novel network design
algorithms, aggregating existing approaches, and
providing a general framework for a network designer
to test out new proposed resource allocation methods.
In this paper, we present a high-level view of the
OMAN architecture, review specific mathematical
models used in the network representation, and show
how OMAN is used to evaluate tradeoffs in MANET
design. Specifically, we cover three case studies of
optimization. The first case is robust power control
under uncertain channel information for a single
physical layer snapshot. The second case is scheduling
with the availability of directional radiation patterns.
The third case is optimizing topology through
movement planning of relay nodes.
46. Robust Topology Topology engineering concerns with the problem of 2012
Engineering in automatic determination of physical layer parameters to
Multiradio Multichannel form a network with desired properties. In this paper,
Wireless Networks we investigate the joint power control, channel
assignment, and radio interface selection for robust
provisioning of link bandwidth in infrastructure
multiradio multichannel wireless networks in presence
of channel variability and external interference. To
characterize the logical relationship between spatial
contention constraints and transmit power, we
formulate the joint power control and radio-channel
assignment as a generalized disjunctive programming
problem. The generalized Benders decomposition
technique is applied for decomposing the radio-channel
assignment (combinatorial constraints) and network
resource allocation (continuous constraints) so that the
problem can be solved efficiently. The proposed

algorithm is guaranteed to converge to the optimal
solution within a finite number of iterations. We have
evaluated our scheme using traces collected from two
wireless testbeds and simulation studies in Qualnet.
Experiments show that the proposed algorithm is
superior to existing schemes in providing larger
interference margin, and reducing outage and packet
loss probabilities.

47. SenseLess A Database- The 2010 FCC ruling on white spaces proposes relying 2012
Driven White Spaces on a database of incumbents as the primary means of
Network determining white space availability at any white space
device (WSD). While the ruling provides broad
guidelines for the database, the specifics of its design,
features, implementation, and use are yet to be
determined. Furthermore, architecting a network where
all WSDs rely on the database raises several systems
and networking challenges that have remained
unexplored. Also, the ruling treats the database only as
a storehouse for incumbents. We believe that the
mandated use of the database has an additional
opportunity: a means to dynamically manage the RF
spectrum. Motivated by this opportunity, in this paper,
we present SenseLess, a database-driven white spaces
network. As suggested by its very name, in SenseLess,
WSDs rely on a database service to determine white
spaces availability as opposed to spectrum sensing. The
service, using a combination of an up-to-date database
of incumbents, sophisticated signal propagation
modeling, and an efficient content dissemination
mechanism to ensure efficient, scalable, and safe white
space network operation. We build, deploy, and
evaluate SenseLess and compare our results to ground
truth spectrum measurements. We present the unique
system design considerations that arise due to operating
over the white spaces. We also evaluate its efficiency
and scalability. To the best of our knowledge, this is
the first paper that identifies and examines the systems
and networking challenges that arise from operating a
white space network, which is solely dependent on a
channel occupancy database.
48. Smooth Trade-Offs Throughput capacity in mobile ad hoc networks has 2012
between Throughput been studied extensively under many different mobility
and Delay in Mobile Ad models. However, most previous research assumes
Hoc Networks global mobility, and the results show that a constant
per-node throughput can be achieved at the cost of very

high delay. Thus, we are having a very big gap here,
i.e., either low throughput and low delay in static
networks or high throughput and high delay in mobile
networks. In this paper, employing a practical restricted
random mobility model, we try to fill this gap.
Specifically, we assume that a network of unit area
with n nodes is evenly divided into cells with an area of
n -2α, each of which is further evenly divided into
squares with an area of n-2β(0≤ α ≤ β ≤1/2). All nodes
can only move inside the cell which they are initially
distributed in, and at the beginning of each time slot,
every node moves from its current square to a
uniformly chosen point in a uniformly chosen adjacent
square. By proposing a new multihop relay scheme, we
present smooth trade-offs between throughput and
delay by controlling nodes' mobility. We also consider
a network of area nγ (0 ≤ γ ≤ 1) and find that network
size does not affect the results obtained before.
49. Spectrum-Aware Cognitive radio (CR) networks have been proposed as 2012
Mobility Management a solution to both spectrum inefficiency and spectrum
in Cognitive Radio scarcity problems. However, they face several
Cellular Networks challenges based on the fluctuating nature of the
available spectrum, making it more difficult to support
seamless communications, especially in CR cellular
networks. In this paper, a spectrum-aware mobility
management scheme is proposed for CR cellular
networks. First, a novel network architecture is
introduced to mitigate heterogeneous spectrum
availability. Based on this architecture, a unified
mobility management framework is developed to
support diverse mobility events in CR networks, which
consists of spectrum mobility management, user
mobility management, and intercell resource allocation.
The spectrum mobility management scheme
determines a target cell and spectrum band for CR
users adaptively dependent on time-varying spectrum
opportunities, leading to increase in cell capacity. In
the user mobility management scheme, a mobile user
selects a proper handoff mechanism so as to minimize
a switching latency at the cell boundary by considering
spatially heterogeneous spectrum availability. Intercell
resource allocation helps to improve the performance
of both mobility management schemes by efficiently
sharing spectrum resources with multiple cells.
Simulation results show that the proposed method can
achieve better performance than conventional handoff

schemes in terms of both cell capacity as well as
mobility support in communications.
50. Stateless Multicast Multicast routing protocols typically rely on the a priori
Protocol for Ad Hoc creation of a multicast tree (or mesh), which requires
Networks the individual nodes to maintain state information. In
dynamic networks with bursty traffic, where long
periods of silence are expected between the bursts of
data, this multicast state maintenance adds a large
amount of communication, processing, and memory
overhead for no benefit to the application. Thus, we
have developed a stateless receiver-based multicast
(RBMulticast) protocol that simply uses a list of the
multicast members' (e.g., sinks') addresses, embedded
in packet headers, to enable receivers to decide the best
way to forward the multicast traffic. This protocol,
called Receiver-Based Multicast, exploits the
knowledge of the geographic locations of the nodes to
remove the need for costly state maintenance (e.g.,
tree/mesh/neighbor table maintenance), making it
ideally suited for multicasting in dynamic networks.
RBMulticast was implemented in the OPNET
simulator and tested using a sensor network
implementation. Both simulation and experimental
results confirm that RBMulticast provides high success
rates and low delay without the burden of state
maintenance.

TECHNOLOGY : JAVA

DOMAIN : IEEE TRANSACTIONS ON IMAGE PROCESSING

S.NO TITLES DESCRIPTION YEAR
1. Image Super- In this paper, we propose a sparse neighbor selection 2012
Resolution With Sparse scheme for SR reconstruction.We first predetermine a
Neighbor Embedding larger number of neighbors as potential candidates and
develop an extended Robust-SL0 algorithm
tosimultaneously find the neighbors and to solve the
reconstruction weights. Recognizing that the -nearest
neighbor ( -NN) for reconstruction should have similar
local geometric structures basedon clustering, we
employ a local statistical feature, namely histograms
of oriented gradients (HoG) of low-resolution (LR)
image patches, to perform such clustering.
2. Scalable Coding of This paper proposes a novel scheme of scalable 2012

Encrypted Images coding for encrypted images. In the encryption phase,
the original pixel values are masked by a modulo-256
addition with pseudorandom numbers that are derived
from a secret key. Then, the data of quantized sub
image and coefficients are regarded as a set of bit
streams.
3. PDE-Based The proposed model is based on using the single 2012
Enhancement of Color vectors of the gradient magnitude and the second
Images in RGB Space derivatives as a manner to relate different color
components of the image. This model can be viewed
as a generalization of the Bettahar–Stambouli filter to
multivalued images. The proposed algorithm is more
efficient than the mentioned filter and some previous
works at color images denoising and deblurring
without creating false colors
4. Abrupt Motion The robust tracking of abrupt motion is a challenging 2012
Tracking Via task in computer vision due to its large motion
Intensively Adaptive uncertainty. While various particle filters and
Markov-Chain Monte conventional Markov-chain Monte Carlo (MCMC)
Carlo Sampling methods have been proposed for visual tracking, these
methods often suffer from the well-known local-trap
problem or from poor convergence rate. In this paper,
we propose a novel sampling-based tracking scheme
for the abrupt motion problem in the Bayesian
filtering framework. To effectively handle the local-
trap problem, we first introduce the stochastic
approximation Monte Carlo (SAMC) sampling
method into the Bayesian filter tracking framework, in
which the filtering distribution is adaptively estimated
as the sampling proceeds, and thus, a good
approximation to the target distribution is achieved. In
addition, we propose a new MCMC sampler with
intensive adaptation to further improve the sampling
efficiency, which combines a density-grid-based
predictive model with the SAMC sampling, to give a
proposal adaptation scheme. The proposed method is
effective and computationally efficient in addressing
the abrupt motion problem. We compare our approach
with several alternative tracking algorithms, and
extensive experimental results are presented to
demonstrate the effectiveness and the efficiency of the
proposed method in dealing with various types of
abrupt motions.
5. Vehicle Detection in We present an automatic vehicle detection system for 2012
Aerial Surveillance aerial surveillance in this paper. In this system, we
Using Dynamic escape from the stereotype and existing frameworks of

Bayesian Networks vehicle detection in aerial surveillance, which are
either region based or sliding window based. We
design a pixelwise classification method for vehicle
detection. The novelty lies in the fact that, in spite of
performing pixelwise classification, relations among
neighboring pixels in a region are preserved in the
feature extraction process.We consider features
including vehicle colors and local features. For vehicle
color extraction, we utilize a color transform to
separate vehicle colors and nonvehicle colors
effectively. For edge detection, we apply moment
preserving to adjust the thresholds of the Canny edge
detector automatically, which increases the
adaptability and the accuracy for detection in various
aerial images. Afterward, a dynamic Bayesian
network (DBN) is constructed for the classification
purpose. We convert regional local features into
quantitative observations that can be referenced when
applying pixelwise classification via DBN.
Experiments were conducted on a wide variety of
aerial videos. The results demonstrate flexibility and
good generalization abilities of the proposed method
on a challenging data set with aerial surveillance
images taken at different heights and under different
camera angles.
6. A Secret-Sharing- A new blind authentication method based on the secret 2012
Based Method for sharing technique with a data repair capability for
Authentication of grayscale document images via the use of the Portable
Grayscale Document Network Graphics (PNG) image is proposed. An
Images via the Use of authentication signal is generated for each block of a
the PNG Image With a grayscale document image, which, together with the
Data Repair Capability binarized block content, is transformed into several
shares using the Shamir secret sharing scheme. The
involved parameters are carefully chosen so that as
many shares as possible are generated and embedded
into an alpha channel plane. The alpha channel plane
is then combined with the original grayscale image to
form a PNG image. During the embedding process,
the computed share values are mapped into a range of
alpha channel values near their maximum value of 255
to yield a transparent stego-image with a disguise
effect. In the process of image authentication, an
image block is marked as tampered if the
authentication signal computed from the current block
content does not match that extracted from the shares
embedded in the alpha channel plane. Data repairing is

then applied to each tampered block by a reverse
Shamir scheme after collecting two shares from
unmarked blocks. Measures for protecting the security
of the data hidden in the alpha channel are also
proposed. Good experimental results prove the
effectiveness of the proposed method for real
applications.
7. Learn to Personalized Increasingly developed social sharing websites, like
Image Search from the Flickr and Youtube, allow users to create, share,
Photo Sharing annotate and comment medias. The large-scale user-
Websites – projects generated meta-data not only facilitate users in sharing
2012 and organizing multimedia content,but provide useful
information to improve media retrieval and
management. Personalized search serves as one of
such examples where the web search experience is
improved by generating the returned list according to
the modified user search intents. In this paper, we
exploit the social annotations and propose a novel
framework simultaneously considering the user and
query relevance to learn to personalized image search.
The basic premise is to embed the user preference and
query-related search intent into user-specific topic
spaces. Since the users’ original annotation is too
sparse for topic modeling, we need to enrich users’
annotation pool before user-specific topic spaces
construction. The proposed framework contains two
components:
8. A Discriminative Action recognition is very important for many 2012
Model of Motion and applications such as video surveillance, human-
Cross Ratio for View- computer interaction, and so on; view-invariant action
Invariant Action recognition is hot and difficult as well in this field. In
Recognition this paper, a new discriminative model is proposed for
video-based view-invariant action recognition. In the
discriminative model, motion pattern and view
invariants are perfectly fused together to make a better
combination of invariance and distinctiveness. We
address a series of issues, including interest point
detection in image sequence, motion feature extraction
and description, and view-invariant calculation. First,
motion detection is used to extract motion information
from videos, which is much more efficient than
traditional background modeling and tracking-based
methods. Second, as for feature representation, we
exact variety of statistical information from motion
and view-invariant feature based on cross ratio. Last,
in the action modeling, we apply a discriminative

probabilistic model-hidden conditional random field to
model motion patterns and view invariants, by which
we could fuse the statistics of motion and projective
invariability of cross ratio in one framework.
Experimental results demonstrate that our method can
improve the ability to distinguish different categories
of actions with high robustness to view change in real
circumstances.
9. A General Fast In this paper, we propose a general framework for 2012
Registration performance improvement of the current state-of-the-
Framework by art registration algorithms in terms of both accuracy
Learning Deformation– and computation time. The key concept involves rapid
Appearance Correlation prediction of a deformation field for registration
initialization, which is achieved by a statistical
correlation model learned between image appearances
and deformation fields. This allows us to immediately
bring a template image as close as possible to a
subject image that we need to register. The task of the
registration algorithm is hence reduced to estimating
small deformation between the subject image and the
initially warped template image, i.e., the intermediate
template (IT). Specifically, to obtain a good subject-
specific initial deformation, support vector regression
is utilized to determine the correlation between image
appearances and their respective deformation fields.
When registering a new subject onto the template, an
initial deformation field is first predicted based on the
subject's image appearance for generating an IT. With
the IT, only the residual deformation needs to be
estimated, presenting much less challenge to the
existing registration algorithms. Our learning-based
framework affords two important advantages: 1) by
requiring only the estimation of the residual
deformation between the IT and the subject image, the
computation time can be greatly reduced; 2) by
leveraging good deformation initialization, local
minima giving suboptimal solution could be avoided.
Our framework has been extensively evaluated using
medical images from different sources, and the results
indicate that, on top of accuracy improvement,
significant registration speedup can be achieved, as
compared with the case where no prediction of initial
deformation is performed.
10. A Geometric We present a geometric framework for explicit 2012
Construction of derivation of multivariate sampling functions (sinc) on
Multivariate Sinc multidimensional lattices. The approach leads to a

Functions generalization of the link between sinc functions and
the Lagrange interpolation in the multivariate setting.
Our geometric approach also provides a frequency
partition of the spectrum that leads to a nonseparable
extension of the 1-D Shannon (sinc) wavelets to the
multivariate setting. Moreover, we propose a
generalization of the Lanczos window function that
provides a practical and unbiased approach for signal
reconstruction on sampling lattices. While this
framework is general for lattices of any dimension, we
specifically characterize all 2-D and 3-D lattices and
show the detailed derivations for 2-D hexagonal body-
centered cubic (BCC) and face-centered cubic (FCC)
lattices. Both visual and numerical comparisons
validate the theoretical expectations about superiority
of the BCC and FCC lattices over the commonly used
Cartesian lattice.
11. A Novel Algorithm for The challenges in local-feature-based image matching 2012
View and Illumination are variations of view and illumination. Many
Invariant Image methods have been recently proposed to address these
Matching problems by using invariant feature detectors and
distinctive descriptors. However, the matching
performance is still unstable and inaccurate,
particularly when large variation in view or
illumination occurs. In this paper, we propose a view
and illumination invariant image-matching method.
We iteratively estimate the relationship of the relative
view and illumination of the images, transform the
view of one image to the other, and normalize their
illumination for accurate matching. Our method does
not aim to increase the invariance of the detector but
to improve the accuracy, stability, and reliability of
the matching results. The performance of matching is
significantly improved and is not affected by the
changes of view and illumination in a valid range. The
proposed method would fail when the initial view and
illumination method fails, which gives us a new sight
to evaluate the traditional detectors. We propose two
novel indicators for detector evaluation, namely, valid
angle and valid illumination, which reflect the
maximum allowable change in view and illumination,
respectively. Extensive experimental results show that
our method improves the traditional detector
significantly, even in large variations, and the two
indicators are much more distinctive.
12. A Spectral and Spatial This paper presents an algorithm designed to measure 2012

Measure of Local the local perceived sharpness in an image. Our method
Perceived Sharpness in utilizes both spectral and spatial properties of the
Natural Images image: For each block, we measure the slope of the
magnitude spectrum and the total spatial variation.
These measures are then adjusted to account for visual
perception, and then, the adjusted measures are
combined via a weighted geometric mean. The
resulting measure, i.e., S3 (spectral and spatial
sharpness), yields a perceived sharpness map in which
greater values denote perceptually sharper regions.
This map can be collapsed into a single index, which
quantifies the overall perceived sharpness of the whole
image. We demonstrate the utility of the S3 measure
for within-image and across-image sharpness
prediction, no-reference image quality assessment of
blurred images, and monotonic estimation of the
standard deviation of the impulse response used in
Gaussian blurring. We further evaluate the accuracy of
S3 in local sharpness estimation by comparing S3
maps to sharpness maps generated by human subjects.
We show that S3 can generate sharpness maps, which
are highly correlated with the human-subject maps.
13. A Unified Feature and The goal of feature selection is to identify the most 2012
Instance Selection informative features for compact representation,
Framework Using whereas the goal of active learning is to select the
Optimum Experimental most informative instances for prediction. Previous
Design studies separately address these two problems, despite
of the fact that selecting features and instances are
dual operations over a data matrix. In this paper, we
consider the novel problem of simultaneously
selecting the most informative features and instances
and develop a solution from the perspective of
optimum experimental design. That is, by using the
selected features as the new representation and the
selected instances as training data, the variance of the
parameter estimate of a learning function can be
minimized. Specifically, we propose a novel approach,
which is called Unified criterion for Feature and
Instance selection (UFI), to simultaneously identify
the most informative features and instances that
minimize the trace of the parameter covariance matrix.
A greedy algorithm is introduced to efficiently solve
the optimization problem. Experimental results on two
benchmark data sets demonstrate the effectiveness of
our proposed method.
14. An Algorithm for the Speeded-Up Robust Features is a feature extraction 2012

Contextual Adaption of algorithm designed for real-time execution, although
SURF Octave Selection this is rarely achievable on low-power hardware such
With Good Matching as that in mobile robots. One way to reduce the
Performance Best computation is to discard some of the scale-space
Octaves octaves, and previous research has simply discarded
the higher octaves. This paper shows that this
approach is not always the most sensible and presents
an algorithm for choosing which octaves to discard
based on the properties of the imagery. Results
obtained with this best octaves algorithm show that it
is able to achieve a significant reduction in
computation without compromising matching
performance.
15. An Efficient Camera In the field of machine vision, camera calibration 2012
Calibration Technique refers to the experimental determination of a set of
Offering Robustness parameters that describe the image formation process
and Accuracy Over a for a given analytical model of the machine vision
Wide Range of Lens system. Researchers working with low-cost digital
Distortion cameras and off-the-shelf lenses generally favor
camera calibration techniques that do not rely on
specialized optical equipment, modifications to the
hardware, or an a priori knowledge of the vision
system. Most of the commonly used calibration
techniques are based on the observation of a single 3-
D target or multiple planar (2-D) targets with a large
number of control points. This paper presents a novel
calibration technique that offers improved accuracy,
robustness, and efficiency over a wide range of lens
distortion. This technique operates by minimizing the
error between the reconstructed image points and their
experimentally determined counterparts in “distortion
free” space. This facilitates the incorporation of the
exact lens distortion model. In addition, expressing
spatial orientation in terms of unit quaternions greatly
enhances the proposed calibration solution by
formulating a minimally redundant system of
equations that is free of singularities. Extensive
performance benchmarking consisting of both
computer simulation and experiments confirmed
higher accuracy in calibration regardless of the
amount of lens distortion present in the optics of the
camera. This paper also experimentally confirmed that
a comprehensive lens distortion model including
higher order radial and tangential distortion terms
improves calibration accuracy.
16. Bayesian Estimation Structured illumination microscopy is a recent 2012

for Optimized imaging technique that aims at going beyond the
Structured Illumination classical optical resolution by reconstructing high-
Microscopy resolution (HR) images from low-resolution (LR)
images acquired through modulation of the transfer
function of the microscope. The classical
implementation has a number of drawbacks, such as
requiring a large number of images to be acquired and
parameters to be manually set in an ad-hoc manner
that have, until now, hampered its wide dissemination.
Here, we present a new framework based on a
Bayesian inverse problem formulation approach that
enables the computation of one HR image from a
reduced number of LR images and has no specific
constraints on the modulation. Moreover, it permits to
automatically estimate the optimal reconstruction
hyperparameters and to compute an uncertainty bound
on the estimated values. We demonstrate through
numerical evaluations on simulated data and examples
on real microscopy data that our approach represents a
decisive advance for a wider use of HR microscopy
through structured illumination.
17. Binarization of Low- It is difficult to directly apply existing binarization 2012
Quality Barcode approaches to the barcode images captured by mobile
Images Captured by device due to their low quality. This paper proposes a
Mobile Phones Using novel scheme for the binarization of such images. The
Local Window of barcode and background regions are differentiated by
Adaptive Location and the number of edge pixels in a search window. Unlike
Size existing approaches that center the pixel to be
binarized with a window of fixed size, we propose to
shift the window center to the nearest edge pixel so
that the balance of the number of object and
background pixels can be achieved. The window size
is adaptive either to the minimum distance to edges or
minimum element width in the barcode. The threshold
is calculated using the statistics in the window. Our
proposed method has demonstrated its capability in
handling the nonuniform illumination problem and the
size variation of objects. Experimental results
conducted on 350 images captured by five mobile
phones achieve about 100% of recognition rate in
good lighting conditions, and about 95% and 83% in
bad lighting conditions. Comparisons made with nine
existing binarization methods demonstrate the
advancement of our proposed scheme
18. B-Spline Explicit A new formulation of active contours based on 2012
Active Surfaces An explicit functions has been recently suggested. This

Efficient Framework novel framework allows real-time 3-D segmentation
for Real-Time 3-D since it reduces the dimensionality of the segmentation
Region-Based problem. In this paper, we propose a B-spline
Segmentation formulation of this approach, which further improves
the computational efficiency of the algorithm. We also
show that this framework allows evolving the active
contour using local region-based terms, thereby
overcoming the limitations of the original method
while preserving computational speed. The feasibility
of real-time 3-D segmentation is demonstrated using
simulated and medical data such as liver computer
tomography and cardiac ultrasound images.
19. Change Detection in This paper presents an unsupervised distribution-free 2012
Synthetic Aperture change detection approach for synthetic aperture radar
Radar Images based on (SAR) images based on an image fusion strategy and a
Image Fusion and novel fuzzy clustering algorithm. The image fusion
Fuzzy Clustering technique is introduced to generate a difference image
by using complementary information from a mean-
ratio image and a log-ratio image. In order to restrain
the background information and enhance the
information of changed regions in the fused difference
image, wavelet fusion rules based on an average
operator and minimum local area energy are chosen to
fuse the wavelet coefficients for a low-frequency band
and a high-frequency band, respectively. A
reformulated fuzzy local-information C-means
clustering algorithm is proposed for classifying
changed and unchanged regions in the fused
difference image. It incorporates the information about
spatial context in a novel fuzzy way for the purpose of
enhancing the changed information and of reducing
the effect of speckle noise. Experiments on real SAR
images show that the image fusion strategy integrates
the advantages of the log-ratio operator and the mean-
ratio operator and gains a better performance. The
change detection results obtained by the improved
fuzzy clustering algorithm exhibited lower error than
its preexistences.

20. Color Constancy for Color constancy algorithms are generally based on the 2012
Multiple Light Sources simplifying assumption that the spectral distribution of
a light source is uniform across scenes. However, in
reality, this assumption is often violated due to the
presence of multiple light sources. In this paper, we
will address more realistic scenarios where the
uniform light-source assumption is too restrictive.

First, a methodology is proposed to extend existing
algorithms by applying color constancy locally to
image patches, rather than globally to the entire
image. After local (patch-based) illuminant estimation,
these estimates are combined into more robust
estimations, and a local correction is applied based on
a modified diagonal model. Quantitative and
qualitative experiments on spectral and real images
show that the proposed methodology reduces the
influence of two light sources simultaneously present
in one scene. If the chromatic difference between
these two illuminants is more than 1° , the proposed
framework outperforms algorithms based on the
uniform light-source assumption (with error-reduction
up to approximately 30%). Otherwise, when the
chromatic difference is less than 1° and the scene can
be considered to contain one (approximately) uniform
light source, the performance of the proposed method
framework is similar to global color constancy
methods.
21. Coupled Bias–Variance Subspace-based face representation can be looked as a 2012
Tradeoff for Cross- regression problem. From this viewpoint, we first
Pose Face Recognition revisited the problem of recognizing faces across pose
differences, which is a bottleneck in face recognition.
Then, we propose a new approach for cross-pose face
recognition using a regressor with a coupled bias-
variance tradeoff. We found that striking a coupled
balance between bias and variance in regression for
different poses could improve the regressor-based
cross-pose face representation, i.e., the regressor can
be more stable against a pose difference. With the
basic idea, ridge regression and lasso regression are
explored. Experimental results on CMU PIE, the
FERET, and the Multi-PIE face databases show that
the proposed bias-variance tradeoff can achieve
considerable reinforcement in recognition
performance
22. Depth From Motion Space-variantly blurred images of a scene contain 2012
and Optical Blur With valuable depth information. In this paper, our
an Unscented Kalman objective is to recover the 3-D structure of a scene
Filter from motion blur/optical defocus. In the proposed
approach, the difference of blur between two
observations is used as a cue for recovering depth,
within a recursive state estimation framework. For
motion blur, we use an unblurred-blurred image pair.
Since the relationship between the observation and the

scale factor of the point spread function associated
with the depth at a point is nonlinear, we propose and
develop a formulation of unscented Kalman filter for
depth estimation. There are no restrictions on the
shape of the blur kernel. Furthermore, within the same
formulation, we address a special and challenging
scenario of depth from defocus with translational
jitter. The effectiveness of our approach is evaluated
on synthetic as well as real data, and its performance
is also compared with contemporary techniques.
23. Design of Almost It is a well-known fact that (compact-support) dyadic 2012
Symmetric Orthogonal wavelets [based on the two channel filter banks (FBs)]
Wavelet Filter Bank cannot be simultaneously orthogonal and symmetric.
Via Direct Although orthogonal wavelets have the energy
Optimization preservation property, biorthogonal wavelets are
preferred in image processing applications because of
their symmetric property. In this paper, a novel
method is presented for the design of almost
symmetric orthogonal wavelet FB. Orthogonality is
structurally imposed by using the unnormalized lattice
structure, and this leads to an objective function,
which is relatively simple to optimize. The designed
filters have good frequency response, flat group delay,
almost symmetric filter coefficients, and symmetric
wavelet function
24. Design of Interpolation Traditionally, subpixel interpolation in stereo-vision 2012
Functions for Subpixel- systems was designed for the block-matching
Accuracy Stereo- algorithm. During the evaluation of different
Vision Systems interpolation strategies, a strong correlation was
observed between the type of the stereo algorithm and
the subpixel accuracy of the different solutions.
Subpixel interpolation should be adapted to each
stereo algorithm to achieve maximum accuracy. In
consequence, it is more important to propose
methodologies for interpolation function generation
than specific function shapes. We propose two such
methodologies based on data generated by the stereo
algorithms. The first proposal uses a histogram to
model the environment and applies histogram
equalization to an existing solution adapting it to the
data. The second proposal employs synthetic images
of a known environment and applies function fitting to
the resulted data. The resulting function matches the
algorithm and the data as best as possible. An
extensive evaluation set is used to validate the
findings. Both real and synthetic test cases were

employed in different scenarios. The test results are
consistent and show significant improvements
compared with traditional solutions.

25. Entropy-Functional- In this paper, an entropy-functional-based online 2012
Based Online Adaptive adaptive decision fusion (EADF) framework is
Decision Fusion developed for image analysis and computer vision
Framework With applications. In this framework, it is assumed that the
Application to Wildfire compound algorithm consists of several
Detection in Video subalgorithms, each of which yields its own decision
as a real number centered around zero, representing
the confidence level of that particular subalgorithm.
Decision values are linearly combined with weights
that are updated online according to an active fusion
method based on performing entropic projections onto
convex sets describing subalgorithms. It is assumed
that there is an oracle, who is usually a human
operator, providing feedback to the decision fusion
method. A video-based wildfire detection system was
developed to evaluate the performance of the decision
fusion algorithm. In this case, image data arrive
sequentially, and the oracle is the security guard of the
forest lookout tower, verifying the decision of the
combined algorithm. The simulation results are
presented.
26. Fast Semantic Exploring context information for visual recognition 2012
Diffusion for Large- has recently received significant research attention.
Scale Context-Based This paper proposes a novel and highly efficient
Image and Video approach, which is named semantic diffusion, to
Annotation utilize semantic context for large-scale image and
video annotation. Starting from the initial annotation
of a large number of semantic concepts (categories),
obtained by either machine learning or manual
tagging, the proposed approach refines the results
using a graph diffusion technique, which recovers the
consistency and smoothness of the annotations over a
semantic graph. Different from the existing graph-
based learning methods that model relations among
data samples, the semantic graph captures context by
treating the concepts as nodes and the concept
affinities as the weights of edges. In particular, our
approach is capable of simultaneously improving
annotation accuracy and adapting the concept
affinities to new test data. The adaptation provides a
means to handle domain change between training and
test data, which often occurs in practice. Extensive

experiments are conducted to improve concept
annotation results using Flickr images and TV
program videos. Results show consistent and
significant performance gain (10 on both image and
video data sets). Source codes of the proposed
algorithms are available online.
27. Gradient-Based Image A major problem in imaging applications such as 2012
Recovery Methods magnetic resonance imaging and synthetic aperture
From Incomplete radar is the task of trying to reconstruct an image with
Fourier Measurements the smallest possible set of Fourier samples, every
single one of which has a potential time and/or power
cost. The theory of compressive sensing (CS) points to
ways of exploiting inherent sparsity in such images in
order to achieve accurate recovery using sub-Nyquist
sampling schemes. Traditional CS approaches to this
problem consist of solving total-variation (TV)
minimization programs with Fourier measurement
constraints or other variations thereof. This paper
takes a different approach. Since the horizontal and
vertical differences of a medical image are each more
sparse or compressible than the corresponding TV
image, CS methods will be more successful in
recovering these differences individually. We develop
an algorithm called GradientRec that uses a CS
algorithm to recover the horizontal and vertical
gradients and then estimates the original image from
these gradients. We present two methods of solving
the latter inverse problem, i.e., one based on least-
square optimization and the other based on a
generalized Poisson solver. After a thorough
derivation of our complete algorithm, we present the
results of various experiments that compare the
effectiveness of the proposed method against other
leading methods.
28. Groupwise Registration Groupwise registration is concerned with bringing a 2012
of Multimodal Images group of images into the best spatial alignment. If
by an Efficient Joint images in the group are from different modalities, then
Entropy Minimization the intensity correspondences across the images can be
Scheme modeled by the joint density function (JDF) of the
cooccurring image intensities. We propose a so-called
treecode registration method for groupwise alignment
of multimodal images that uses a hierarchical
intensity-space subdivision scheme through which an
efficient yet sufficiently accurate estimation of the
(high-dimensional) JDF based on the Parzen kernel
method is computed. To simultaneously align a group

of images, a gradient-based joint entropy minimization
was employed that also uses the same hierarchical
intensity-space subdivision scheme. If the Hilbert
kernel is used for the JDF estimation, then the
treecode method requires no data-dependent
bandwidth selection and is thus fully automatic. The
treecode method was compared with the ensemble
clustering (EC) method on four different publicly
available multimodal image data sets and on a
synthetic monomodal image data set. The obtained
results indicate that the treecode method has similar
and, for two data sets, even superior performances
compared to the EC method in terms of registration
error and success rate. The obtained good registration
performances can be mostly attributed to the
sufficiently accurate estimation of the JDF, which is
computed through the hierarchical intensity-space
subdivision scheme, that captures all the important
features needed to detect the correct intensity
correspondences across a multimodal group of images
undergoing registration.
29. Higher Degree Total We introduce novel image regularization penalties to 2012
Variation (HDTV) overcome the practical problems associated with the
Regularization for classical total variation (TV) scheme. Motivated by
Image Recovery novel reinterpretations of the classical TV regularizer,
we derive two families of functionals involving higher
degree partial image derivatives; we term these
families as isotropic and anisotropic higher degree TV
(HDTV) penalties, respectively. The isotropic penalty
is the mixed norm of the directional image derivatives,
while the anisotropic penalty is the separable norm of
directional derivatives. These functionals inherit the
desirable properties of standard TV schemes such as
invariance to rotations and translations, preservation
of discontinuities, and convexity. The use of mixed
norms in isotropic penalties encourages the joint
sparsity of the directional derivatives at each pixel,
thus encouraging isotropic smoothing. In contrast, the
fully separable norm in the anisotropic penalty ensures
the preservation of discontinuities, while continuing to
smooth along the line like features; this scheme thus
enhances the linenlike image characteristics analogous
to standard TV. We also introduce efficient majorize-
minimize algorithms to solve the resulting
optimization problems. The numerical comparison of
the proposed scheme with classical TV penalty,

current second-degree methods, and wavelet
algorithms clearly demonstrate the performance
improvement. Specifically, the proposed algorithms
minimize the staircase and ringing artifacts that are
common with TV and wavelet schemes, while better
preserving the singularities. We also observe that
anisotropic HDTV penalty provides consistently
improved reconstructions compared with the isotropic
HDTV penalty.
30. Human Identification This paper presents a new approach to improve the 2012
Using Finger Images performance of finger-vein identification systems
presented in the literature. The proposed system
simultaneously acquires the finger-vein and low-
resolution fingerprint images and combines these two
evidences using a novel score-level combination
strategy. We examine the previously proposed finger-
vein identification approaches and develop a new
approach that illustrates it superiority over prior
published efforts. The utility of low-resolution
fingerprint images acquired from a webcam is
examined to ascertain the matching performance from
such images. We develop and investigate two new
score-level combinations, i.e., holistic and nonlinear
fusion, and comparatively evaluate them with more
popular score-level fusion approaches to ascertain
their effectiveness in the proposed system. The
rigorous experimental results presented on the
database of 6264 images from 156 subjects illustrate
significant improvement in the performance, i.e., both
from the authentication and recognition experiments.
31. Image Fusion Using A novel higher order singular value decomposition 2012
Higher Order Singular (HOSVD)-based image fusion algorithm is proposed.
Value Decomposition The key points are given as follows: 1) Since image
fusion depends on local information of source images,
the proposed algorithm picks out informative image
patches of source images to constitute the fused image
by processing the divided subtensors rather than the
whole tensor; 2) the sum of absolute values of the
coefficients (SAVC) from HOSVD of subtensors is
employed for activity-level measurement to evaluate
the quality of the related image patch; and 3) a novel
sigmoid-function-like coefficient-combining scheme
is applied to construct the fused result. Experimental
results show that the proposed algorithm is an
alternative image fusion approach.

32. Image Segmentation Active contour models (ACMs) integrated with 2012
Based on the Poincaré various kinds of external force fields to pull the
Map Method contours to the exact boundaries have shown their
powerful abilities in object segmentation. However,
local minimum problems still exist within these
models, particularly the vector field's “equilibrium
issues.” Different from traditional ACMs, within this
paper, the task of object segmentation is achieved in a
novel manner by the Poincaré map method in a
defined vector field in view of dynamical systems. An
interpolated swirling and attracting flow (ISAF) vector
field is first generated for the observed image. Then,
the states on the limit cycles of the ISAF are located
by the convergence of Newton-Raphson sequences on
the given Poincaré sections. Meanwhile, the periods of
limit cycles are determined. Consequently, the objects'
boundaries are represented by integral equations with
the corresponding converged states and periods.
Experiments and comparisons with some traditional
external force field methods are done to exhibit the
superiority of the proposed method in cases of
complex concave boundary segmentation, multiple-
object segmentation, and initialization flexibility. In
addition, it is more computationally efficient than
traditional ACMs by solving the problem in some
lower dimensional subspace without using level-set
methods.

33. Implicit Polynomial This paper presents a simple distance estimation for 2012
Representation implicit polynomial fitting. It is computed as the
Through a Fast Fitting height of a simplex built between the point and the
Error Estimation surface (i.e., a triangle in 2-D or a tetrahedron in 3-D),
which is used as a coarse but reliable estimation of the
orthogonal distance. The proposed distance can be
described as a function of the coefficients of the
implicit polynomial. Moreover, it is differentiable and
has a smooth behavior . Hence, it can be used in any
gradient-based optimization. In this paper, its use in a
Levenberg-Marquardt framework is shown, which is
particularly devoted for nonlinear least squares
problems. The proposed estimation is a generalization
of the gradient-based distance estimation, which is
widely used in the literature. Experimental results,
both in 2-D and 3-D data sets, are provided.
Comparisons with state-of-the-art techniques are
presented, showing the advantages of the proposed

approach.

34. Integrating In this paper, we propose a method to exploit 2012
Segmentation segmentation information for elastic image
Information for registration using a Markov-random-field (MRF)-
Improved MRF-Based based objective function. MRFs are suitable for
Elastic Image discrete labeling problems, and the labels are defined
Registration as the joint occurrence of displacement fields (for
registration) and segmentation class probability. The
data penalty is a combination of the image intensity
(or gradient information) and the mutual dependence
of registration and segmentation information. The
smoothness is a function of the interaction between
the defined labels. Since both terms are a function of
registration and segmentation labels, the overall
objective function captures their mutual dependence.
A multiscale graph-cut approach is used to achieve
subpixel registration and reduce the computation time.
The user defines the object to be registered in the
floating image, which is rigidly registered before
applying our method. We test our method on synthetic
image data sets with known levels of added noise and
simulated deformations, and also on natural and
medical images. Compared with other registration
methods not using segmentation information, our
proposed method exhibits greater robustness to noise
and improved registration accuracy.

35. Iterative Narrowband- In this paper, an iterative narrow-band-based graph 2012
Based Graph Cuts cuts (INBBGC) method is proposed to optimize the
Optimization for geodesic active contours with region forces
Geodesic Active (GACWRF) model for interactive object
Contours With Region segmentation. Based on cut metric on graphs proposed
Forces (GACWRF) by Boykov and Kolmogorov, an NBBGC method is
devised to compute the local minimization of GAC.
An extension to an iterative manner, namely,
INBBGC, is developed for less sensitivity to the initial
curve. The INBBGC method is similar to graph-cuts-
based active contour (GCBAC) presented by Xu , and
their differences have been analyzed and discussed.
We then integrate the region force into GAC. An
improved INBBGC (IINBBGC) method is proposed
to optimize the GACWRF model, thus can effectively
deal with the concave region and complicated real-
world images segmentation. Two region force models

such as mean and probability models are studied.
Therefore, the GCBAC method can be regarded as the
special case of our proposed IINBBGC method
without region force. Our proposed algorithm has
been also analyzed to be similar to the Grabcut
method when the Gaussian mixture model region
force is adopted, and the band region is extended to
the whole image. Thus, our proposed IINBBGC
method can be regarded as narrow-band-based
Grabcut method or GCBAC with region force method.
We apply our proposed IINBBGC algorithm on
synthetic and real-world images to emphasize its
performance, compared with other segmentation
methods, such as GCBAC and Grabcut methods.
36. PDE-Based A novel method for color image enhancement is 2012
Enhancement of Color proposed as an extension of the scalar-diffusion-
Images in RGB Space shock-filter coupling model, where noisy and blurred
images are denoised and sharpened. The proposed
model is based on using the single vectors of the
gradient magnitude and the second derivatives as a
manner to relate different color components of the
image. This model can be viewed as a generalization
of the Bettahar-Stambouli filter to multivalued images.
The proposed algorithm is more efficient than the
mentioned filter and some previous works at color
images denoising and deblurring without creating
false colors.
37. Polyview Fusion A We propose a simple but effective strategy that aims 2012
Strategy to Enhance to enhance the performance of existing video
Video-Denoising denoising algorithms, i.e., polyview fusion (PVF). The
Algorithms idea is to denoise the noisy video as a 3-D volume
using a given base 2-D denoising algorithm but
applied from multiple views (front, top, and side
views). A fusion algorithm is then designed to merge
the resulting multiple denoised videos into one, so that
the visual quality of the fused video is improved.
Extensive tests using a variety of base video-denoising
algorithms show that the proposed PVF method leads
to surprisingly significant and consistent gain in terms
of both peak signal-to-noise ratio (PSNR) and
structural similarity (SSIM) performance, particularly
at high noise levels, where the improvement over
state-of-the-art denoising algorithms is often more
than 2 dB in PSNR.

38. Preconditioning for We propose a simple preconditioning method for 2012

Edge-Preserving Image accelerating the solution of edge-preserving image
Super Resolution super-resolution (SR) problems in which a linear shift-
invariant point spread function is employed. Our
technique involves reordering the high-resolution
(HR) pixels in a similar manner to what is done in
preconditioning methods for quadratic SR
formulations. However, due to the edge preserving
requirements, the Hessian matrix of the cost function
varies during the minimization process. We develop
an efficient update scheme for the preconditioner in
order to cope with this situation. Unlike some other
acceleration strategies that round the displacement
values between the low-resolution (LR) images on the
HR grid, the proposed method does not sacrifice the
optimality of the observation model. In addition, we
describe a technique for preconditioning SR problems
involving rational magnification factors. The use of
such factors is motivated in part by the fact that, under
certain circumstances, optimal SR zooms are
nonintegers. We show that, by reordering the pixels of
the LR images, the structure of the problem to solve is
modified in such a way that preconditioners based on
circulant operators can be used.
39. PSF Estimation via This paper proposes an efficient method to estimate 2012
Gradient Domain the point spread function (PSF) of a blurred image
Correlation using image gradients spatial correlation. A patch-
based image degradation model is proposed for
estimating the sample covariance matrix of the
gradient domain natural image. Based on the fact that
the gradients of clean natural images are
approximately uncorrelated to each other, we
estimated the autocorrelation function of the PSF from
the covariance matrix of gradient domain blurred
image using the proposed patch-based image
degradation model. The PSF is computed using a
phase retrieval technique to remove the ambiguity
introduced by the absence of the phase. Experimental
results show that the proposed method significantly
reduces the computational burden in PSF estimation,
compared with existing methods, while giving
comparable blurring kernel
40. Rigid-Motion-Invariant This paper studies the problem of 3-D rigid-motion- 2012
Classification of 3-D invariant texture discrimination for discrete 3-D
Textures textures that are spatially homogeneous by modeling
them as stationary Gaussian random fields. The latter
property and our formulation of a 3-D rigid motion of

a texture reduce the problem to the study of 3-D
rotations of discrete textures. We formally develop the
concept of 3-D texture rotations in the 3-D digital
domain. We use this novel concept to define a
"distance" between 3-D textures that remains invariant
under all 3-D rigid motions of the texture. This
concept of "distance" can be used for a monoscale or a
mill tiscale 3-D rigid- motion-invariant testing of the
statistical similarity of the 3-D textures. To compute
the "distance" between any two rotations R1 and R2 of
two given 3-D textures, we use the Kullback-Leibler
divergence between 3-D Gaussian Markov random
fields fitted to the rotated texture data. Then, the 3-D
rigid-motion-invariant texture distance is the integral
average, with respect to the Haar measure of the group
SO(3), of all of these divergences when rotations R1
and R2 vary throughout SO(3). We also present an
algorithm enabling the computation of the proposed 3-
D rigid-motion-invariant texture distance as well as
rules for 3-D rigid-motion-invariant texture
discrimination/classification and experimental results
demonstrating the capabilities of the proposed 3-D
rigid-motion texture discrimination rules when applied
in a multiscale setting, even on very general 3-D
texture models.

41. Robust Image Hashing In this paper, we propose a robust-hash function based 2012
Based on Random on random Gabor filtering and dithered lattice vector
Gabor Filtering and quantization (LVQ). In order to enhance the
Dithered Lattice Vector robustness against rotation manipulations, the
Quantization conventional Gabor filter is adapted to be rotation
invariant, and the rotation-invariant filter is
randomized to facilitate secure feature extraction.
Particularly, a novel dithered-LVQ-based quantization
scheme is proposed for robust hashing. The dithered-
LVQ-based quantization scheme is well suited for
robust hashing with several desirable features,
including better tradeoff between robustness and
discrimination, higher randomness, and secrecy,
which are validated by analytical and experimental
results. The performance of the proposed hashing
algorithm is evaluated over a test image database
under various content-preserving manipulations. The
proposed hashing algorithm shows superior robustness
and discrimination performance compared with other
state-of-the-art algorithms, particularly in the

robustness against rotations (of large degrees).
42. Snakes With an We present a new class of continuously defined 2012
Ellipse-Reproducing parametric snakes using a special kind of exponential
Property splines as basis functions. We have enforced our bases
to have the shortest possible support subject to some
design constraints to maximize efficiency. While the
resulting snakes are versatile enough to provide a
good approximation of any closed curve in the plane,
their most important feature is the fact that they admit
ellipses within their span. Thus, they can perfectly
generate circular and elliptical shapes. These features
are appropriate to delineate cross sections of
cylindrical-like conduits and to outline bloblike
objects. We address the implementation details and
illustrate the capabilities of our snake with synthetic
and real data.

TECHNOLOGY : JAVA

DOMAIN : IEEE TRANSACTIONS ON SOFTWARE
ENGINEERING

1. Automated Behavioral We present a technique to test Java refactoring 2012
Testing of Refactoring engines. It automates test input generation by using a
Engines Java program generator that exhaustively generates
programs for a given scope of Java declarations. The
refactoring under2test is applied to each generated
program. The technique uses SAFEREFACTOR, a
tool for detecting behavioral changes, as oracle to
evaluate the correctness of these transformations.
2. Towards This study contributes to the literature by considering 2012
Comprehensible 15 different Bayesian Network (BN) classifiers and
Software Fault comparing them to other popular machine learning
Prediction Models techniques. Furthermore, the applicability of the
Using Bayesian Markov blanket principle for feature selection, which
Network Classifiers is a natural extension to BN theory, is investigated.
3. Using Dependency In this paper, we present a family of test case 2012
Structures for prioritisation techniques that use the dependency
Prioritisation of information from a test suite to prioritise that test
Functional Test Suites suite. The nature of the techniques preserves the
dependencies in the test ordering.
4. Automatically Dynamic specification mining observes program 2012
Generating Test Cases executions to infer models of normal program
for Specification behavior. What makes us believe that we have seen

Mining sufficiently many executions? The TAUTOKO
(“Tautoko” is the Mãori word for “enhance, enrich.”)
typestate miner generates test cases that cover
previously unobserved behavior, systematically
extending the execution space, and enriching the
specification. To our knowledge, this is the first
combination of systematic test case generation and
typestate mining-a combination with clear benefits:
On a sample of 800 defects seeded into six Java
subjects, a static typestate verifier fed with enriched
models would report significantly more true positives
and significantly fewer false positives than the initial
models
5. Fault Localization for In recent years, there has been significant interest in 2012
Dynamic Web fault-localization techniques that are based on
Applications statistical analysis of program constructs executed by
passing and failing executions. This paper shows how
the Tarantula, Ochiai, and Jaccard fault-localization
algorithms can be enhanced to localize faults
effectively in web applications written in PHP by
using an extended domain for conditional and
function-call statements and by using a source
mapping. We also propose several novel test-
generation strategies that are geared toward producing
test suites that have maximal fault-localization
effectiveness. We implemented various fault-
localization techniques and test-generation strategies
in Apollo, and evaluated them on several open-source
PHP applications. Our results indicate that a variant of
the Ochiai algorithm that includes all our
enhancements localizes 87.8 percent of all faults to
within 1 percent of all executed statements, compared
to only 37.4 percent for the unenhanced Ochiai
algorithm. We also found that all the test-generation
strategies that we considered are capable of generating
test suites with maximal fault-localization
effectiveness when given an infinite time budget for
test generation. However, on average, a directed
strategy based on path-constraint similarity achieves
this maximal effectiveness after generating only 6.5
tests, compared to 46.8 tests for an undirected test-
generation strategy.

TECHNOLOGY : JAVA

DOMAIN : IEEE TRANSACTIONS ON GRID & CLOUD COMPUTING

1. Business-OWL This paper introduces the Business-OWL (BOWL), an 2012
(BOWL)—A ontology rooted in the Web Ontology Language
Hierarchical Task (OWL), and modeled as a Hierarchical Task Network
Network Ontology for (HTN) for the dynamic formation of business
Dynamic Business processes
Process Decomposition
and Formulation
2. Detecting And The advent of emerging computing technologies such 2012
Resolving Firewall as service-oriented architecture and cloud computing
Policy Anomalies has enabled us to perform business services more
efficiently and effectively.
3. Online System for Grid In this paper, we present the design and evaluation of 2012
Resource Monitoring system architecture for grid resource monitoring and
and Machine Learning- prediction. We discuss the key issues for system
Based Prediction implementation, including machine learning-based
methodologies for modeling and optimization of
resource prediction models.
4. SOAP Processing SOAP communications produce considerable network 2011
Performance and traffic, making them unfit for distributed, loosely
Enhancement coupled and heterogeneous computing environments
such as the open Internet. They introduce higher
latency and processing delays than other technologies,
like Java RMI & CORBA. WS research has recently
focused on SOAP performance enhancement.
5. Weather data sharing Intelligent agents can play an important role in helping 2011
system: an agent-based achieve the ‘data grid’ vision. In this study, the
distributed data authors present a multi-agent-based framework to
management implement manage, share and query weather data in a
geographical distributed environment, named weather
data sharing system
6. pCloud: A Distributed In this paper we present pCloud, a distributed system 2012
System for Practical that constitutes the ?rst attempt towards practical
PIR cPIR. Our approach assumes a disk-based architecture
that retrieves one page with a single query. Using a
striping technique, we distribute the database to a
number of cooperative peers, and leverage their
computational resources to process cPIR queries in
parallel. We implemented pCloud on the PlanetLab
network, and experimented extensively with several
system parameters. Results

7. A Gossip Protocol for We address the problem of dynamic resource 2012
Dynamic Resource management for a large-scale cloud environment. Our
Management in Large contribution includes outlining a distributed
Cloud Environments. middleware architecture and presenting one of its key
elements: a gossip protocol that (1) ensures fair
resource allocation among sites/applications, (2)
dynamically adapts the allocation to load changes and
(3) scales both in the number of physical machines
and sites/applications.
8. A Novel Process In this paper, we explore a novel approach to model 2012
Network Model for dynamic behaviors of interacting context-aware web
Interacting Context- services. It aims to effectively process and take
aware Web Services advantage of contexts and realize behavior adaptation
of web services, further to facilitate the development
of context-aware application of web services.
9. Monitoring and Recently, several mobile services are changing to 2012
Detecting Abnormal cloud-based mobile services with richer
Behavior in Mobile communications and higher flexibility. We present a
new mobile cloud infrastructure that combines mobile
Cloud Infrastructure devices and cloud services. This new infrastructure
provides virtual mobile instances through cloud
computing. To commercialize new services with this
infrastructure, service providers should be aware of
security issues. Here, we first define new mobile cloud
services through mobile cloud infrastructure and
discuss possible security threats through the use of
several service scenarios. Then, we propose a
methodology and architecture for detecting abnormal
behavior through the monitoring of both host and
network data. To validate our methodology, we
injected malicious programs into our mobile cloud test
bed and used a machine learning algorithm to detect
the abnormal behavior that arose from these programs.

10. Impact of Storage The volume of worldwide digital content has 2012
Acquisition Intervals increased nine-fold within the last five years, and this
on the Cost-Efficiency immense growth is predicted to continue in
of the Private vs. Public foreseeable future eaching 8ZB already by 2015.
Storage. Traditionally, in order to cope with the growing
demand for storage capacity, organizations proactively
built and managed their private storage facilities.
Recently, with the proliferation of public cloud
infrastructure offerings, many organizations, instead,
welcomed the alternative of outsourcing their storage
needs to the providers of public cloud storage services.
The comparative cost-efficiency of these two

alternatives depends on a number of factors, among
which are e.g. the prices of the public and private
storage, the charging and the storage acquisition
intervals, and the predictability of the demand for
storage. In this paper, we study how the cost-
efficiency of the private vs. public storage depends on
the acquisition interval at which the organization re-
assesses
its storage needs and acquires additional private
storage. The analysis in the paper suggests that the
shorter the acquisition interval, the more likely it is
that the private storage solution is less expensive as
compared with the public cloud infrastructure. This
phenomenon is also illustrated in the paper
numerically using the storage needs encountered by a
university back-up and archiving service as an
example. Since the acquisition interval is determined
by the organization’s ability to foresee the growth of
storage demand, by the provisioning schedules of
storage equipment providers, and by internal practices
of the organization, among other factors, the
organization owning a private storage solution may
want to control some of these factors in order to attain
a shorter acquisition interval and thus make the private
storage (more) cost-efficient..
11. Managing A Cloud for We present a novel execution environment for 2012
Multi-agent Systems on multiagent systems building on concepts from cloud
Ad-hoc Networks computing and peer-to-peer networks. The novel
environment can provide the computing power of a
cloud for multi-agent systems in intermittently
connected networks. We present the design and
implementation of a prototype operating system for
managing the environment. The operating system
provides the user with a consistent view of a single
machine, a single file system, and a unified
programming model while providing elasticity and
availability.
12. Cloud Computing The use of cloud computing has increased rapidly in 2012
Security: From Single many organizations. Cloud computing provides many
to benefits in terms of low cost and accessibility of data.
Multi-Clouds Ensuring the security of cloud computing is a major
factor in the cloud computing environment, as users
often store sensitive information with cloud storage
providers but these providers may be untrusted.
Dealing with “single cloud” providers is predicted to
become less popular with customers due to risks of

service availability failure and the possibility of
malicious insiders in the single cloud. A movement
towards “multi-clouds”, or in other words,
“interclouds” or “cloud-ofclouds”
has emerged recently. This paper surveys recent
research related to single and multi-cloud security and
addresses possible solutions. It is found that the
research into the use of multicloud providers to
maintain security has received less attention from the
research community than has the use of single clouds.
This work aims to promote the use of multi-clouds
due to its ability to reduce security risks that affect the
cloud computing user.
13. Optimization of In cloud computing, cloud providers can offer cloud 2012
Resource Provisioning consumers two provisioning plans for computing
Cost in Cloud resources, namely reservation and on-demand plans.
Computing In general, cost of utilizing computing resources
provisioned by reservation plan is cheaper than that
provisioned by on-demand plan, since cloud consumer
has to pay to provider in advance. With the reservation
plan, the consumer can reduce the total resource
provisioning cost. However, the best advance
reservation of resources is difficult to be achieved due
to uncertainty of consumer's future demand and
providers' resource prices. To address this problem, an
optimal cloud resource provisioning (OCRP)
algorithm is proposed by formulating a stochastic
programming model. The OCRP algorithm can
provision computing resources for being used in
multiple provisioning stages as well as a long-term
plan, e.g., four stages in a quarter plan and twelve
stages in a yearly plan. The demand and price
uncertainty is considered in OCRP. In this paper,
different approaches to obtain the solution of the
OCRP algorithm are considered including
deterministic equivalent formulation, sample-average
approximation, and Benders decomposition.
Numerical studies are extensively performed in which
the results clearly show that with the OCRP algorithm,
cloud consumer can successfully minimize total cost
of resource provisioning in cloud computing
environments
14. A Secure Erasure A cloud storage system, consisting of a collection of 2012
Code-Based Cloud storage servers, provides long-term storage services
Storage System with over the Internet.Storing data in a third party’s cloud
Secure Data system causes serious concern over data

Forwarding confidentiality. General encryption schemes protect
data confidentiality, but also limit the functionality of
the storage system because a few operations are
supported over encrypted data. Constructing a secure
storage system that supports multiple functions is
challenging when the storage system is distributed and
has no central authority. We propose a threshold proxy
re-encryption scheme and integrate it with a
decentralized erasure code such that a secure
distributed storage system is formulated. The
distributed storage system not only supports secure
and robust data storage and retrieval, but also lets a
user forward his data in the storage servers to another
user without retrieving the data back. The main
technical contribution is that the proxy re-encryption
scheme supports encoding operations over encrypted
messages as well as forwarding operations over
encoded and encrypted messages. Our method fully
integrates encrypting, encoding, and forwarding. We
analyze and suggest suitable parameters for the
number of copies of a message dispatched to storage
servers and the number of storage servers queried by a
key server. These parameters allow more flexible
adjustment between the number of storage servers .

15. HASBE: A Cloud computing has emerged as one of the most 2012
Hierarchical Attribute- influential paradigms in the IT industry in recent
Based Solution for years. Since this
Flexible and Scalable new computing technology requires users to entrust
Access Control in their valuable data to cloud providers, there have been
Cloud Computing increasing security and privacy concerns on
outsourced data. Several schemes employing attribute-
based encryption (ABE) have been proposed for
access control of outsourced data in cloud computing;
however, most of them suffer from inflexibility in
implementing complex access control policies. In
order to realize scalable, flexible, and fine-grained
access control of outsourced data in cloud computing,
in this paper, we propose hierarchical attribute-set-
based encryption (HASBE) by extending ciphertext-
policy attribute-set-based encryption (ASBE) with a
hierarchical structure of users. The proposed scheme
not only achieves scalability due to its hierarchical
structure, but also inherits flexibility and fine-grained
access control in supporting compound attributes of
ASBE. In addition, HASBE employs multiple value

assignments for access expiration time to deal with
user revocation more efficiently than existing
schemes. We formally prove the security of HASBE
based on security of the ciphertext-policy attribute-
based encryption (CP-ABE) scheme by Bethencourt et
al. and analyze its performance and computational
complexity. We implement our scheme and show that
it is both efficient and flexible in dealing with access
control for outsourced data in cloud computing with
comprehensive experiments.
16. A Distributed Access The large-scale, dynamic, and heterogeneous nature of 2012
Control Architecture cloud computing poses numerous security challenges.
for Cloud Computing But the cloud's main challenge is to provide a robust
authorization mechanism that incorporates
multitenancy and virtualization aspects of resources.
The authors present a distributed architecture that
incorporates principles from security management and
software engineering and propose key requirements
and a design model for the architecture.

17. Cloud Computing The use of cloud computing has increased rapidly in 2012
Security: From Single many organizations. Cloud computing provides many
to Multi-clouds benefits in terms of low cost and accessibility of data.
Ensuring the security of cloud computing is a major
factor in the cloud computing environment, as users
often store sensitive information with cloud storage
providers but these providers may be untrusted.
Dealing with "single cloud" providers is predicted to
become less popular with customers due to risks of
service availability failure and the possibility of
malicious insiders in the single cloud. A movement
towards "multi-clouds", or in other words,
"interclouds" or "cloud-of-clouds" has emerged
recently. This paper surveys recent research related to
single and multi-cloud security and addresses possible
solutions. It is found that the research into the use of
multi-cloud providers to maintain security has
received less attention from the research community
than has the use of single clouds. This work aims to
promote the use of multi-clouds due to its ability to
reduce security risks that affect the cloud computing
user.
18. Scalable and Secure Personal health record (PHR) is an emerging patient- 2012
Sharing of Personal centric model of health information exchange, which
Health Records in is often outsourced to be stored at a third party, such
Cloud Computing as cloud providers. However, there have been wide

using Attribute-based privacy concerns as personal health information could
Encryption be exposed to those third party servers and to
unauthorized parties. To assure the patients’ control
over access to their own PHRs, it is a promising
method to encrypt the PHRs before outsourcing. Yet,
issues such as risks of privacy exposure, scalability in
key management, flexible access and efficient user
revocation, have remained the most important
challenges toward achieving fine-grained,
cryptographically enforced data access control. In this
paper, we propose a novel patient-centric framework
and a suite of mechanisms for data access control to
PHRs stored in semi-trusted servers. To achieve fine-
grained and scalable data access control for PHRs, we
leverage attribute based encryption (ABE) techniques
to encrypt each patient’s PHR file. Different from
previous works in secure data outsourcing, we focus
on the multiple data owner scenario, and divide the
users in the PHR system into multiple security
domains that greatly reduces the key management
complexity for owners and users. A high degree of
patient privacy is guaranteed simultaneously by
exploiting multi-authority ABE. Our scheme also
enables dynamic modification of access policies or file
attributes, supports efficient on-demand user/attribute
revocation and break-glass access under emergency
scenarios. Extensive analytical and experimental
results are presented which show the security,
scalability and efficiency of our proposed scheme
19. Cloud Data Production Offering strong data protection to cloud users while 2012
for Masses enabling rich applications is a challenging task. We
explore a new cloud platform architecture called Data
Protection as a Service, which dramatically reduces
the per-application development effort required to
offer data protection, while still allowing rapid
development and maintenance.

20. Secure and Practical Cloud Computing has great potential of providing 2012
Outsourcing of Linear robust computational power to the society at reduced
Programming in Cloud cost. It enables customers with limited computational
Computing resources to outsource their large computation
workloads to the cloud, and economically enjoy the
massive computational power, bandwidth, storage,

and even appropriate software that can be shared in a
pay-per-use manner. Despite the tremendous benefits,
security is the primary obstacle that prevents the wide
adoption of this promising computing model,
especially for customers when their confidential data
are consumed and produced during the computation.
Treating the cloud as an intrinsically insecure
computing platform from the viewpoint of the cloud
customers, we must design mechanisms that not only
protect sensitive information by enabling
computations with encrypted data, but also protect
customers from malicious behaviors by enabling the
validation of the computation result. Such a
mechanism of general secure computation outsourcing
was recently shown to be feasible in theory, but to
design mechanisms that are practically efficient
remains a very challenging problem. Focusing on
engineering computing and optimization tasks, this
paper investigates secure outsourcing of widely
applicable linear programming (LP) computations. In
order to achieve practical efficiency, our mechanism
design explicitly decomposes the LP computation
outsourcing into public LP solvers running on the
cloud and private LP parameters owned by the
customer. The resulting flexibility allows us to explore
appropriate security/ efficiency tradeoff via higher-
level abstraction of LP computations than the general
circuit representation. In particular, by formulating
private data owned by the customer for LP problem as
a set of matrices and vectors, we are able to develop a
set of efficient privacy-preserving problem
transformation techniques, which allow customers to
transform original LP problem into some arbitrary one
while protecting sensitive input/output information.
To validate the computation result, we further explore
the fundamental duality theorem of LP computation
and derive the necessary and sufficient conditions that
correct result must satisfy. Such result verification
mechanism is extremely efficient and incurs close-to-
zero additional cost on both cloud server and
customers. Extensive security analysis and experiment
results show the immediate practicability of our
mechanism design.
21. Efficient audit service Cloud-based outsourced storage relieves the client’s 2012
outsourcing for data burden for storage management and maintenance by
integrity in clouds – providing a comparably low-cost, scalable, location-

projects 2012 independent platform. However, the fact that clients
no longer have physical possession of data indicates
that they are facing a potentially formidable risk for
missing or corrupted data. To avoid the security risks,
audit services are critical to ensure the integrity and
availability of outsourced data and to achieve digital
forensics and credibility on cloud computing. Provable
data possession (PDP), which is a cryptographic
technique for verifying the integrity of data without
retrieving it at an untrusted server, can be used to
realize audit services. In this paper, profiting from the
interactive zero-knowledge proof system, we address
the construction of an interactive PDP protocol to
prevent the fraudulence of prover (soundness
property) and the leakage of verified data (zero-
knowledge property). We prove that our construction
holds these properties based on the computation
Diffie–Hellman assumption and the rewindable black-
box knowledge extractor. We also propose an efficient
mechanism with respect to probabilistic queries and
periodic verification to reduce the audit costs per
verification and implement abnormal detection timely.
In addition, we present an efficient method for
selecting an optimal parameter value to minimize
computational overheads of cloud audit services. Our
experimental results demonstrate the effectiveness of
our approach
22. Efficient audit service Cloud-based outsourced storage relieves the client’s 2012
outsourcing for data burden for storage management and maintenance by
integrity in clouds – providing a comparably low-cost, scalable, location-
projects 2012 independent platform. However, the fact that clients
no longer have physical possession of data indicates
that they are facing a potentially formidable risk for
missing or corrupted data. To avoid the security risks,
audit services are critical to ensure the integrity and
availability of outsourced data and to achieve digital
forensics and credibility on cloud computing. Provable
data possession (PDP), which is a cryptographic
technique for verifying the integrity of data without
retrieving it at an untrusted server, can be used to
realize audit services. In this paper, profiting from the
interactive zero-knowledge proof system, we address
the construction of an interactive PDP protocol to
prevent the fraudulence of prover (soundness
property) and the leakage of verified data (zero-
knowledge property). We prove that our construction

holds these properties based on the computation
Diffie–Hellman assumption and the rewindable black-
box knowledge extractor. We also propose an efficient
mechanism with respect to probabilistic queries and
periodic verification to reduce the audit costs per
verification and implement abnormal detection timely.
In addition, we present an efficient method for
selecting an optimal parameter value to minimize
computational overheads of cloud audit services. Our
experimental results demonstrate the effectiveness of
our approach.

23. Secure and privacy Cloud storage services enable users to remotely access 2012
preserving keyword data in a cloud anytime and anywhere, using any
searching for cloud device, in a pay-as-you-go manner. Moving data into a
storage services – cloud offers great convenience to users since they do
projects 2012 not have to care about the large capital investment in
both the deployment and management of the hardware
infrastructures. However, allowing a cloud service
provider (CSP), whose purpose is mainly for making a
profit, to take the custody of sensitive data, raises
underlying security and privacy issues. To keep user
data confidential against an untrusted CSP, a natural
way is to apply cryptographic approaches, by
disclosing the data decryption key only to authorized
users. However, when a user wants to retrieve files
containing certain keywords using a thin client, the
adopted encryption system should not only support
keyword searching over encrypted data, but also
provide high performance. In this paper, we
investigate the characteristics of cloud storage services
and propose a secure and privacy preserving keyword
searching (SPKS) scheme, which allows the CSP to
participate in the decipherment, and to return only
files containing certain keywords specified by the
users, so as to reduce both the computational and
communication overhead in decryption for users, on
the condition of preserving user data privacy and user
querying privacy. Performance analysis shows that the
SPKS scheme is applicable to a cloud environment
24. Secure and privacy Cloud storage services enable users to remotely access 2012
preserving keyword data in a cloud anytime and anywhere, using any
searching for cloud device, in a pay-as-you-go manner. Moving data into a
storage services – cloud offers great convenience to users since they do
projects 2012 not have to care about the large capital investment in

both the deployment and management of the hardware
infrastructures. However, allowing a cloud service
provider (CSP), whose purpose is mainly for making a
profit, to take the custody of sensitive data, raises
underlying security and privacy issues. To keep user
data confidential against an untrusted CSP, a natural
way is to apply cryptographic approaches, by
disclosing the data decryption key only to authorized
users. However, when a user wants to retrieve files
containing certain keywords using a thin client, the
adopted encryption system should not only support
keyword searching over encrypted data, but also
provide high performance. In this paper, we
investigate the characteristics of cloud storage services
and propose a secure and privacy preserving keyword
searching (SPKS) scheme, which allows the CSP to
participate in the decipherment, and to return only
files containing certain keywords specified by the
users, so as to reduce both the computational and
communication overhead in decryption for users, on
the condition of preserving user data privacy and user
querying privacy. Performance analysis shows that the
SPKS scheme is applicable to a cloud environment

25. Cooperative Provable Provable data possession (PDP) is a technique for 2012
Data Possession for ensuring the integrity of data in storage outsourcing.
Integrity Verification in In this paper, we address the construction of an
Multi-Cloud Storage efficient PDP scheme for distributed cloud storage to
support the scalability of service and data migration,
in which we consider the existence of multiple cloud
service providers to cooperatively store and maintain
the clients’ data. We present a cooperative
PDP (CPDP) scheme based on homomorphic
verifiable response and hash index hierarchy. We
prove the security of our scheme based on multi-
prover zero-knowledge proof system, which can
satisfy completeness, knowledge soundness, and zero-
knowledge properties. In addition, we articulate
performance optimization mechanisms for our
scheme, and in particular present an efficient method
for selecting optimal parameter values to minimize the
computation costs of clients and storage service
providers. Our experiments show that our solution
introduces lower computation and communication
overheads in comparison with non-cooperative

approaches
26. Cooperative Provable Provable data possession (PDP) is a technique for 2012
Data Possession for ensuring the integrity of data in storage outsourcing.
Integrity Verification in In this paper, we address the construction of an
Multi-Cloud Storage efficient PDP scheme for distributed cloud storage to
support the scalability of service and data migration,
in which we consider the existence of multiple cloud
service providers to cooperatively store and maintain
the clients’ data. We present a cooperative
PDP (CPDP) scheme based on homomorphic
verifiable response and hash index hierarchy. We
prove the security of our scheme based on multi-
prover zero-knowledge proof system, which can
satisfy completeness, knowledge soundness, and zero-
knowledge properties. In addition, we articulate
performance optimization mechanisms for our
scheme, and in particular present an efficient method
for selecting optimal parameter values to minimize the
computation costs of clients and storage service
providers. Our experiments show that our solution
introduces lower computation and communication
overheads in comparison with non-cooperative
approaches
27. Bootstrapping Ontologies have become the de-facto modeling tool of 2012
Ontologies for Web choice, employed in many applications and
Services – projects prominently in the semantic web. Nevertheless,
2012 ontology construction remains a daunting task.
Ontological bootstrapping, which aims at
automatically generating concepts and their relations
in a given domain, is a promising technique for
ontology construction. Bootstrapping an ontology
based on a set of predefined textual sources, such as
web services, must address the problem of multiple,
largely unrelated concepts. In this paper, we propose
an ontology bootstrapping process for web services.
We exploit the advantage that web services usually
consist of both WSDL and free text descriptors. The
WSDL descriptor is evaluated using two methods,
namely Term Frequency/Inverse Document Frequency
(TF/IDF) and web context generation. Our proposed
ontology bootstrapping process integrates the results
of both methods and applies a third method to validate
the concepts using the service free text descriptor,
thereby offering a more accurate definition of
ontologies. We extensively validated our
bootstrapping method using a large repository of real-

world web services and verified the results against
existing ontologies. The experimental results indicate
high precision. Furthermore, the recall versus
precision comparison of the results when each method
is separately implemented presents the advantage of
our integrated bootstrapping approach.
28. Data Security and It is well-known that cloud computing has many 2012
Privacy Protection potential advantages and many enterprise applications
Issues in Cloud and data are migrating to public or hybrid cloud. But
Computing regarding some business-critical applications, the
organizations, especially large enterprises, still
wouldn't move them to cloud. The market size the
cloud computing shared is still far behind the one
expected. From the consumers' perspective, cloud
computing security concerns, especially data security
and privacy protection issues, remain the primary
inhibitor for adoption of cloud computing services.
This paper provides a concise but all-round analysis
on data security and privacy protection issues
associated with cloud computing across all stages of
data life cycle. Then this paper discusses some current
solutions. Finally, this paper describes future research
work about data security and privacy protection issues
in cloud.
29. Stochastic models of Cloud computing services are becoming ubiquitous, 2012
load balancing and and are starting to serve as the primary source of
scheduling in cloud computing power for both enterprises and personal
computing clusters computing applications. We consider a stochastic
model of a cloud computing cluster, where jobs arrive
according to a stochastic process and request virtual
machines (VMs), which are specified in terms of
resources such as CPU, memory and storage space.
While there are many design issues associated with
such systems, here we focus only on resource
allocation problems, such as the design of algorithms
for load balancing among servers, and algorithms for
scheduling VM configurations. Given our model of a
cloud, we first define its capacity, i.e., the maximum
rates at which jobs can be processed in such a system.
Then, we show that the widely-used Best-Fit
scheduling algorithm is not throughput-optimal, and
present alternatives which achieve any arbitrary
fraction of the capacity region of the cloud. We then
study the delay performance of these alternative
algorithms through simulations.
30. A comber approach to Cloud computing is an internet based pay as use 2012

protect cloud service which provides three layered services
computing against (Software as a Service, Platform as a Service and
XML DDoS and HTTP Infrastructure as a Service) to its consumers on
DDoS attack demand. These on demand service facilities provide to
its consumers in multitenant environment but as
facility increases complexity and security problems
also increase. Here all the resources are at one place in
data centers. Cloud uses public and private APIs
(Application Programming Interface) to provide
services to its consumers in multitenant environment.
In this environment Distributed Denial of Service
attack (DDoS), especially HTTP, XML or REST
based DDoS attacks may be very dangerous and may
provide very harmful effects for availability of
services and all consumers will get affected at the
same time. One other reason is that because the cloud
computing users make their request in XML then send
this request using HTTP protocol and build their
system interface with REST protocol such as Amazon
EC2 or Microsoft Azure. So the threaten coming from
distributed REST attacks are more and easy to
implement by the attacker, but to security expert very
difficult to resolve. So to resolve these attacks this
paper introduces a comber approach for security
services called filtering tree. This filtering tree has five
filters to detect and resolve XML and HTTP DDoS
attack
31. Resource allocation Cloud computing is a platform that hosts applications 2012
and scheduling in cloud and services for businesses and users to accesses
computing computing as a service. In this paper, we identify two
scheduling and resource allocation problems in cloud
computing. We describe Hadoop MapReduce and its
schedulers, and present recent research efforts in this
area including alternative schedulers and
enhancements to existing schedulers. The second
scheduling problem is the provisioning of virtual
machines to resources in the cloud. We present a
survey of the different approaches to solve this
resource allocation problem. We also include recent
research and standards for inter-connecting clouds and
discuss the suitability of running scientific
applications in the cloud.
32. Application study of Aimed at some problems in Network Education 2012
online education Resources Construction at present, we analyse the
platform based on characteristics and application range of cloud
cloud computing computing, and present an integrated solving scheme.

On that basis, some critical technologies such as the
cloud storage, streaming media and cloud safety are
analyzed in detail. Finally, the paper gives
summarization and expectation.
33. Towards temporal Access control is one of the most important security 2012
access control in cloud mechanisms in cloud computing. Attribute-based
computing access control provides a flexible approach that allows
data owners to integrate data access policies within the
encrypted data. However, little work has been done to
explore temporal attributes in specifying and
enforcing the data owner's policy and the data user's
privileges in cloud-based environments. In this paper,
we present an efficient temporal access control
encryption scheme for cloud services with the help of
cryptographic integer comparisons and a proxy-based
re-encryption mechanism on the current time. We also
provide a dual comparative expression of integer
ranges to extend the power of attribute expression for
implementing various temporal constraints. We prove
the security strength of the proposed scheme and our
experimental results not only validate the
effectiveness of our scheme, but also show that the
proposed integer comparison scheme performs
significantly better than previous bitwise comparison
scheme.
34. Privacy-Preserving We come up with a digital rights management (DRM) 2012
DRM for Cloud concept for cloud computing and show how license
Computing management for software within the cloud can be
achieved in a privacy-friendly manner. In our
scenario, users who buy software from software
providers stay anonymous. At the same time, our
approach guarantees that software licenses are bound
to users and their validity is checked before execution.
We employ a software re-encryption scheme so that
computing centers which execute users' software are
not able to build user profiles - not even under
pseudonym - of their users. We combine secret
sharing and homomorphic encryption. We make sure
that malicious users are unable to relay software to
others. DRM constitutes an incentive for software
providers to take partin a future cloud computing
scenario. We make this scenario more attractive for
users by preserving their privacy.
35. Pricing and peak aware The proposed cloud computing scheduling algorithms 2012
scheduling algorithm demonstrated feasibility of interactions between
for cloud computing distributors and one of their heavy use customers in a

smart grid environment. Specifically, the proposed
algorithms take cues from the dynamic pricing and
schedule the jobs/tasks in ways that the energy usage
is what distributors are hinted. In addition, a peak
threshold can be dynamically assigned such that the
energy usage at any given time will not exceed the
threshold. The proposed scheduling algorithm proved
the feasibility of managing the energy usage of cloud
computers in collaboration with the energy distributor
36. Comparison of Computer Networks face a constant struggle against 2012
Network Intrusion intruders and attackers. Attacks on distributed systems
Detection Systems in grow stronger and more prevalent each and every day.
cloud computing Intrusion detection methods are a key to control and
environment potentially eradicate attacks on a system. An Intrusion
detection system pertains to the methods used to
identify an attack on a computer or computer network.
In cloud computing environment the applications are
user-centric and the customers should be confident
about their applications stored in the cloud server.
Network Intrusion Detection System (NIDS) plays an
important role in providing the network security. They
provide a defence layer which monitors the network
traffic for pre-defined suspicious activity or pattern. In
this paper Snort, Tcpdump and Network Flight
Recorder which are the most famous NIDS in cloud
system are examined and contrasted.
37. Intelligent and Active Cloud's development has entered the practical stage, 2012
Defense Strategy of but safety issues must be resolved. How to avoid the
Cloud Computing risk on the web page, how to prevent attacks from
hacker, how to protect user data in the cloud. This
paper discusses some satety solution :the credit level
of web page, Trace data, analyze and filter them by
large-scale statistical methods, encryption protection
of user data and key management.
38. Distributed Shared In this paper we discuss the idea of combining 2012
Memory as an wireless sensor networks and cloud computing starting
Approach for with a state of the art analysis of existing approaches
Integrating WSNs and in this field. As result of the analysis we propose to
Cloud Computing reflect a real wireless sensor network by virtual
sensors in the cloud. The main idea is to replicate data
stored on the real sensor nodes also in the virtual
sensors, without explicit triggering such updates from
the application. We provide a short overview of the
resulting architecture before explaining mechanisms to
realize it. The means to ensure a certain level of
consistency between the real WSN and the virtual

sensors in the cloud is distributed shared memory. In
order to realize DSM in WSNs we have developed a
middleware named tinyDSM which is shortly
introduced here and which provides means for
replicating sensor data and ensuring the consistency of
the replicates. Even though tinyDSM is a pretty good
vehicle to realize our idea there are some open issues
that need to be addressed when realizing such an
architecture. We discuss these challenges in an
abstract way to ensure clear separation between the
idea and its specific realization.

39. Improving resource Even though the adoption of cloud computing and 2012
allocation in multi-tier virtualization have improved resource utilization to a
cloud systems great extent, the continued traditional approach of
resource allocation in production environments has
introduced the problem of over-provisioning of
resources for enterprise-class applications hosted in
cloud systems. In this paper, we address the problem
and propose ways to minimize over-provisioning of IT
resources in multi-tier cloud systems by adopting an
innovative approach of application performance
monitoring and resource allocation at individual tier
levels, on the basis of criticality of the business
services and availability of the resources at one's
disposal.

40. Ensuring Distributed Cloud computing enables highly scalable services to 2012
Accountability for Data be easily consumed over the Internet on an as-needed
Sharing in the Cloud basis. A major feature of the cloud services is that
users' data are usually processed remotely in unknown
machines that users do not own or operate. While
enjoying the convenience brought by this new
emerging technology, users' fears of losing control of
their own data (particularly, financial and health data)
can become a significant barrier to the wide adoption
of cloud services. To address this problem, in this
paper, we propose a novel highly decentralized
information accountability framework to keep track of
the actual usage of the users' data in the cloud. In
particular, we propose an object-centered approach
that enables enclosing our logging mechanism
together with users' data and policies. We leverage the
JAR programmable capabilities to both create a
dynamic and traveling object, and to ensure that any
access to users' data will trigger authentication and

automated logging local to the JARs. To strengthen
user's control, we also provide distributed auditing
mechanisms. We provide extensive experimental
studies that demonstrate the efficiency and
effectiveness of the proposed approaches.
41. Efficient information Cloud computing as an emerging technology trend is 2012
retrieval for ranked expected to reshape the advances in information
queries in cost- technology. In this paper, we address two fundamental
effective cloud issues in a cloud environment: privacy and efficiency.
environments We first review a private keyword-based file retrieval
scheme proposed by Ostrovsky et. al. Then, based on
an aggregation and distribution layer (ADL), we
present a scheme, termed efficient information
retrieval for ranked query (EIRQ), to further reduce
querying costs incurred in the cloud. Queries are
classified into multiple ranks, where a higher ranked
query can retrieve a higher percentage of matched
files. Extensive evaluations have been conducted on
an analytical model to examine the effectiveness of
our scheme.

TECHNOLOGY : JAVA

DOMAIN : IEEE TRANSACTIONS ON MULTIMEDIA

1. Movie2Comics: This paper proposes a scheme that is able to 2012
Towards a Lively
automatically turn a movie clip to comics. Two
Video Content
principles are followed in the scheme: 1) optimizing
Presentation the information preservation of the movie; and 2)
generating outputs following the rules and the styles
of comics. The scheme mainly contains three
components: script-face mapping, descriptive picture
extraction, and cartoonization. The script-face
mapping utilizes face tracking and recognition
techniques to accomplish the mapping between
characters’ faces and their scripts
2. Robust Watermarking In this paper, we propose a robust watermarking 2012
of Compressed and algorithm to watermark JPEG2000 compressed and
Encrypted JPEG2000 encrypted images. The encryption algorithm we
Images propose to use is a stream cipher. While the proposed
technique embeds watermark in the compressed-
encrypted domain, the extraction ofwatermark can be

done in the decrypted domain
3. Load-Balancing Multipath Switching systems (MPS) are intensely
Multipath Switching used in state-of-the-art core routers to provide terabit
System with Flow Slice or even petabit switching capacity. One of the most
intractable issues in designing MPS is how to load
balance traffic across its multiple paths while not
disturbing the intraflow packet orders. Previous
packet-based solutions either suffer from delay
penalties or lead to O(N2 ) hardware complexity,
hence do not scale. Flow-based hashing algorithms
also perform badly due to the heavy-tailed flow-size
distribution. In this paper, we develop a novel scheme,
namely, Flow Slice (FS) that cuts off each flow into
flow slices at every intraflow interval larger than a
slicing threshold and balances the load on a finer
granularity. Based on the studies of tens of real
Internet traces, we show that setting a slicing threshold
of 1-4 ms, the FS scheme achieves comparative load-
balancing performance to the optimal one. It also
limits the probability of out-of-order packets to a
negligible level (10-6) on three popular MPSes at the
cost of little hardware complexity and an internal
speedup up to two. These results are proven by
theoretical analyses and also validated through trace-
driven prototype simulations
4. Robust Face-Name Automatic face identification of characters in movies 2012
Graph Matching for has drawn significant research interests and led to
Movie Character many interesting applications. It is a challenging
Identification problem due to the huge variation in the appearance of
each character. Although existing methods
demonstrate promising results in clean environment,
the performances are limited in complex movie scenes
due to the noises generated during the face tracking
and face clustering process. In this paper we present
two schemes of global face-name matching based
framework for robust character identification. The
contributions of this work include: Complex character
changes are handled by simultaneously graph partition
and graph matching. Beyond existing character
identification approaches, we further perform an in-
depth sensitivity analysis by introducing two types of
simulated noises. The proposed schemes demonstrate
state-of-the-art performance on movie character
identification in various genres of movies.
5. Learn to Personalized Increasingly developed social sharing websites, like 2012
Image Search from the Flickr and Youtube, allow users to create, share,

Photo Sharing annotate and comment medias. The large-scale user-
Websites – projects generated meta-data not only facilitate users in sharing
2012 and organizing multimedia content,but provide useful
information to improve media retrieval and
management. Personalized search serves as one of
such
examples where the web search experience is
improved by generating the returned list according to
the modified user search intents. In this paper, we
exploit the social annotations and propose a novel
framework simultaneously considering the user and
query relevance to learn to personalized image search.
The basic premise is to embed the user preference and
query-related
search intent into user-specific topic spaces. Since the
users’ original annotation is too sparse for topic
modeling, we need to enrich users’ annotation pool
before user-specific topic spaces construction. The
proposed framework contains two components:

Algorithm Solved IEEE Projects 2012 2013 Java @ Seabirdssolutions

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