Java Projects Ieee Projects

NCCT
Promise for the Best Projects

IEEE Transaction Papers
Abstract enclosed
For Complete Paper, Pl contact us

IEEE Papers – 2009, 2008, 2007 and so on

To Search specific year
Use Ctrl + F and specify year
It will give year wise results

e.g – Ctrl + F and mention 2009, you will get 25+ Projects

IEEE TRANSACTIONS ON MOBILE COMPUTING, VOL. 8, NO. 2, FEBRUARY
2009

CONTENTION-AWARE PERFORMANCE ANALYSIS OF
MOBILITY-ASSISTED ROUTING

A large body of work has theoretically analyzed the performance of
mobility-assisted routing schemes for intermittently connected mobile
networks.
However, the vast majority of these prior studies have ignored wireless
contention. Recent papers have shown through simulations that
ignoring contention leads to inaccurate and misleading results, even
for sparse networks.
In this paper, we analyze the performance of routing schemes under
contention. First, we introduce a mathematical framework to model
contention. This framework can be used to analyze any routing scheme
with any mobility and channel model.
Then, we use this framework to compute the expected delays for
different representative mobility-assisted routing schemes under
random direction, random waypoint, and community-based mobility
models.
Finally, we use these delay expressions to optimize the design of
routing schemes while demonstrating that designing and optimizing
routing schemes using analytical expressions that ignore contention
can lead to suboptimal or even erroneous behavior.

Index Terms
Delay-tolerant networks, wireless contention, performance analysis,
mobility-assisted routing.

IEEE TRANSACTIONS ON MOBILE COMPUTING, VOL. 8, NO. 6,
JUNE 2009

OPPORTUNISTIC SCHEDULING WITH
RELIABILITY GUARANTEES IN COGNITIVE
RADIO NETWORKS

We develop opportunistic scheduling policies for
cognitive radio networks that maximize the throughput
utility of the secondary (unlicensed) users subject to
maximum collision constraints with the primary (licensed)
users.
We consider a cognitive network with static primary users
and potentially mobile secondary users. We use the
technique of Lyapunov Optimization to design an online
flow control, scheduling, and resource allocation
algorithm that meets the desired objectives and provides
explicit performance guarantees.

Index Terms
Cognitive radio, queuing analysis, resource allocation,
Lyapunov optimization.

IEEE TRANSACTIONS ON MOBILE COMPUTING, VOL. 8, NO. 3, MARCH 2009

A FLEXIBLE PRIVACY-ENHANCED
LOCATION-BASED SERVICES SYSTEM
FRAMEWORK AND PRACTICE

Location-based services (LBSs) are becoming increasingly important to the
success and attractiveness of next-generation wireless systems. However, a
natural tension arises between the need for user privacy and the flexible use
of location information.
In this paper, we present a framework to support privacy-enhanced LBSs. We
classify the services according to several basic criteria, and we propose a
hierarchical key distribution method to support these services. The main idea
behind the system is to hierarchically encrypt location information under
different keys, and distribute the appropriate keys only to group members
with the necessary permission.
Four methods are proposed to deliver hierarchical location information while
maintaining privacy. We propose a key tree rebalancing algorithm to maintain
the rekeying performance of the group key management. Furthermore, we
present a practical LBS system implementation.
Hierarchical location information coding offers flexible location information
access which enables a rich set of LBSs. Our load tests show such a system
is highly practical with good efficiency and scalability.

Index Terms
Location-based services, location privacy, social networks, hierarchical key
distribution

WATERMARKING RELATIONAL DATABASES USING
OPTIMIZATION BASED TECHNIQUES

Proving ownership rights on outsourced relational databases is a
crucial issue in today internet-based application environments and
in many content distribution applications.
In this paper, we present a mechanism for proof of ownership
based on the secure embedding of a robust imperceptible
watermark in relational data. We formulate the watermarking of
relational databases as a constrained optimization problem, and
discuss efficient techniques to solve the optimization problem and
to handle the constraints.
Our watermarking technique is resilient to watermark
synchronization errors because it uses a partitioning approach
that does not require marker tuples. Our approach overcomes a
major weakness in previously proposed watermarking techniques.
Watermark decoding is based on a threshold-based technique
characterized by an optimal threshold that minimizes the
probability of decoding errors.
We implemented a proof of concept implementation of our
watermarking technique and showed by experimental results that
our technique is resilient to tuple deletion, alteration and insertion
attacks.

Keywords:
Watermarking, Digital Rights, Optimization

IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, VOL. 19,
NO. 7, JULY 2008

QUIVER: CONSISTENT OBJECT SHARING FOR
EDGE SERVICES

We present Quiver, a system that coordinates service proxies placed at the
“edge” of the Internet to serve distributed clients accessing a service
involving mutable objects. Quiver enables these proxies to perform
consistent accesses to shared objects by migrating the objects to proxies
performing operations on those objects.
These migrations dramatically improve performance when operations
involving an object exhibit geographic locality, since migrating this object
into the vicinity of proxies hosting these operations will benefit all such
operations.
Other workloads benefit from Quiver, dispersing the computation load across
the proxies and saving the costs of sending operation parameters over the
wide area when these are large.
Quiver also supports optimizations for single-object reads that do not
involve migrating the object. We detail the protocols for implementing object
operations and for accommodating the addition, involuntary disconnection,
and voluntary departure of proxies. We also evaluate Quiver through
experiments on PlanetLab.
Finally, we discuss the use of Quiver to build an e-commerce application and
a distributed network traffic modeling service.

Index Terms
Edge services, migration, serializability.

LOCATION-BASED SPATIAL QUERIES WITH DATA
SHARING IN WIRELESS BROADCAST
ENVIRONMENTS

Location-based spatial queries (LBSQs) refer to spatial queries whose
answers rely on the location of the inquirer. Efficient processing of LBSQs is
of critical importance with the ever-increasing deployment and use of mobile
technologies.
We show that LBSQs have certain unique characteristics that traditional
spatial query processing in centralized databases does not address. For
example, a significant challenge is presented by wireless broadcasting
environments, which often exhibit high-latency database access.
In this paper, we present a novel query processing technique that, while
maintaining high scalability and accuracy, manages to reduce the latency
considerably in answering location-based spatial queries.
Our approach is based on peer-to-peer sharing, which enables us to process
queries without delay at a mobile host by using query results cached in its
neighboring mobile peers. We illustrate the appeal of our technique through
extensive simulation results.

IEEE TRANSACTIONS ON MOBILE COMPUTING, VOL. 8, NO. X, XXXXXX 2009

RANDOMCAST: AN ENERGY-EFFICIENT
COMMUNICATION SCHEME FOR MOBILE AD HOC
NETWORKS

Abstract—In mobile ad hoc networks (MANETs), every node overhears every
data transmission occurring in its vicinity and thus, consumes energy
unnecessarily. In IEEE 802.11 Power Saving Mechanism (PSM), a packet must
be advertised before it is actually transmitted.
When a node receives an advertised packet that is not destined to itself, it
switches to a low-power sleep state during the data transmission period, and
thus, avoids overhearing and conserves energy. However, since some
MANET routing protocols such as Dynamic Source Routing (DSR) collect
route information via overhearing, they would suffer if they are used in
combination with 802.11 PSM.
Allowing no overhearing may critically deteriorate the performance of the
underlying routing protocol, while unconditional overhearing may offset the
advantage of using PSM. This paper proposes a new communication
mechanism, called RandomCast, via which a sender can specify the desired
level of overhearing, making a prudent balance between energy and routing
performance.
In addition, it reduces redundant rebroadcasts for a broadcast packet, and
thus, saves more energy. Extensive simulation using ns-2 shows that
RandomCast is highly energy-efficient compared to conventional 802.11 as
well as 802.11 PSM-based schemes, in terms of total energy consumption,
energy goodput, and energy balance.

Index Terms
Energy balance, energy efficiency, mobile ad hoc networks, network lifetime,
overhearing, power saving mechanism

IEEE/ACM TRANSACTIONS ON NETWORKING, VOL. 17, NO. 3, JUNE 2009

ENTROPY BASED ADAPTIVE FLOW AGGREGATION

Internet traffic flow measurement is vitally important for network
management, accounting and performance studies. Cisco’s NetFlow is a
widely deployed flow measurement solution that uses a configurable static
sampling rate to control processor and memory usage on the router and the
amount of reporting flow records generated.
But during flooding attacks the memory and network bandwidth consumed
by flow records can increase beyond what is available.
Currently available countermeasures have their own problems:
1) reject new flows when the cache is full—some legitimate new flows will
not be counted;
2) export not-terminated flows to make room for new ones—this will
exhaust the export bandwidth; and
3) adapt the sampling rate to traffic rate—this will reduce the overall
accuracy of accounting, including legitimate flows.
In this paper, we propose an entropy based adaptive flow aggregation
algorithm. Relying on information- theoretic techniques, the algorithm
efficiently identifies the clusters of attack flows in real time and aggregates
those large number of short attack flows into a few metaflows.
Compared to currently available solutions, our solution not only alleviates
the problem in memory and export bandwidth, but also significantly
improves the accuracy of legitimate flows. Finally, we evaluate our system
using both synthetic trace file and real trace files from the Internet.

Index Terms
Data summarization, information theory, network monitoring, traffic
measurement.

IEEE TRANSACTIONS ON MOBILE COMPUTING
VOL. 8, NO. 1, JANUARY 2009

Geographic ad hoc networks use position information for
routing. They often utilize stateless greedy forwarding and
require the use of recovery algorithms when the greedy
approach fails.
We propose a novel idea based on virtual repositioning of
nodes that allows to increase the efficiency of greedy routing
and significantly increase the success of the recovery
algorithm based on local information alone.
We explain the problem of predicting dead ends, which the
greedy algorithm may reach and bypassing voids in the
network, and introduce Node Elevation Ad hoc Routing
(NEAR), a solution that incorporates both virtual positioning
and routing algorithms that improve performance in ad hoc
networks containing voids.
We demonstrate by simulations the advantages of our
algorithm over other geographic ad hoc routing solutions.

Index Terms
Ad hoc, routing, distributed, elevation, repositioning

IEEE TRANSACTIONS ON NEURAL NETWORKS,
VOL. 20, NO. 3, MARCH 2009 483

ADAPTIVE NEURAL NETWORK TRACKING CONTROL
OF MIMO NONLINEAR SYSTEMS WITH UNKNOWN
DEAD ZONES AND CONTROL DIRECTIONS

In this paper, adaptive neural network (NN) tracking control is investigated
for a class of uncertain multiple-input–multiple- output (MIMO) nonlinear
systems in triangular control structure with unknown nonsymmetric dead
zones and control directions.
The design is based on the principle of sliding mode control and the use of
Nussbaum-type functions in solving the problem of the completely unknown
control directions.
It is shown that the dead-zone output can be represented as a simple linear
system with a static time-varying gain and bounded disturbance by
introducing characteristic function.
By utilizing the integral-type Lyapunov function and introducing an adaptive
compensation term for the upper bound of the optimal approximation error
and the dead-zone disturbance, the closed-loop control system is proved to
be semiglobally uniformly ultimately bounded, with tracking errors
converging to zero under the condition that the slopes of unknown dead
zones are equal. Simulation results demonstrate the effectiveness of the
approach.

Index Terms
Adaptive control, dead zone, neural network (NN) control, Nussbaum
function, sliding mode control.

A FRAMEWORK FOR THE CAPACITY EVALUATION OF
MULTIHOP WIRELESS NETWORKS, 2009

The specific challenges of multihop wireles networks lead to a strong
research effort on efficient protocols design where the offered capacity is a
key objective. More specifically, routing strategy largely impacts the network
capacity, i.e. the throughput offered to each flow.
In this work, we propose a complete framework to compute the upper and the
lower bounds of the network capacity according to a physical topology and a
given routing protocol.
The radio resource sharing principles of CSMA-CA is modeled as a set of
linear constraints with two models of fairness. The first one assumes that
nodes have a fair access to the channel, while the second one assumes that
on the radio links.
We then develop a pessimistic and an optimistic scenarios for radio resource
sharing, yielding a lower bound and an upper bound on the network capacity
for each fairness case.
Our approach is independent of the network topology and the routing
protocols, and provides therefore a relevant framework for their comparison.
We apply our models to a comparative analysis of a well-known flat routing
protocol OLSR against two main self-organized structure approaches, VSR
and localized CDS.

Index Terms
network capacity, multihop wireless networks, upper and lower bounds,
linear programing

IEEE TRANSACTIONS ON BROADCASTING, VOL. 55, NO. 2, JUNE 2009

CONTINUOUS FLOW WIRELESS DATA
BROADCASTING FOR HIGH-SPEED
ENVIRONMENTS

With the increasing popularity of wireless networks and mobile
computing, data broadcasting has emerged as an efficient way of
delivering data to mobile clients having a high degree of commonality
in their demand patterns.
This paper proposes an adaptive wireless push system that operates
efficiently in environments characterized by high broadcasting speeds
and a-priori unknown client demands for data items.
The proposed system adapts to the demand pattern of the client
population in order to reflect the overall popularity of each data
item.We propose a method for feedback collection by the server so that
the client population can enjoy a performance increase in proportion to
the broadcasting speed used by the server.
Simulation results are presented which reveal satisfactory performance
in environments with a-priori unknown client demands and under
various high broadcasting speeds.

Index Terms
Adaptive systems, data broadcasting, high-speed, learning automata.

DYNAMIC AND AUTO RESPONSIVE SOLUTION FOR
DISTRIBUTED DENIAL-OF-SERVICE ATTACKS
DETECTION IN ISP NETWORK, 2009

Denial of service (DoS) attacks and more particularly the distributed ones
(DDoS) are one of the latest threat and pose a grave danger to users,
organizations and infrastructures of the Internet. Several schemes have been
proposed on how to detect some of these attacks, but they suffer from a
range of problems, some of them being impractical and others not being
effective against these attacks.
This paper reports the design principles and evaluation results of our
proposed framework that autonomously detects and accurately characterizes
a wide range of flooding DDoS attacks in ISP network. Attacks are detected
by the constant monitoring of propagation of abrupt traffic changes inside
ISP network.
For this, a newly designed flow-volume based approach (FVBA) is used to
construct profile of the traffic normally seen in the network, and identify
anomalies whenever traffic goes out of profile. Consideration of varying
tolerance factors make proposed detection system scalable to the varying
network conditions and attack loads in real time.
Six-sigma method is used to identify threshold values accurately for
malicious flows characterization. FVBA has been extensively evaluated in a
controlled test-bed environment. Detection thresholds and efficiency is
justified using receiver operating characteristics (ROC) curve.
For validation, KDD 99, a publicly available benchmark dataset is used. The
results show that our proposed system gives a drastic improvement in terms
of detection and false alarm rate.

Index Terms
Distributed Denial of Service Attacks, False Positives, False Negatives, ISP
Network, Network Security

IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
VOL. 8, NO. 2, FEBRUARY 2009

EFFICIENT MULTI-PARTY DIGITAL SIGNATURE USING
ADAPTIVE SECRET SHARING FOR LOW-POWER DEVICES IN
WIRELESS NETWORKS

In this paper, we propose an efficient multi-party signature scheme for
wireless networks where a given number of signees can jointly sign a
document, and it can be verified by any entity who possesses the
certified group public key.
Our scheme is based on an efficient threshold key generation scheme,
which is able to defend against both static and adaptive adversaries.
Specifically, our key generation method employs the bit commitment
technique to achieve efficiency in key generation and share refreshing;
our share refreshing method provides proactive protection to long-
lasting secret and allows a new signee to join a signing group.
We demonstrate that previous known approaches are not efficient in
wireless networks, and the proposed multi-party signature scheme is
flexible, efficient, and achieves strong security for low-power devices in
wireless networks.

Index Terms
Multi-party signature, distributed key generation, elliptic curve
cryptosystems.

GUARANTEED DELIVERY FOR GEOGRAPHICAL
ANYCASTING IN WIRELESS MULTI-SINK SENSOR
AND SENSOR-ACTOR NETWORKS

In the anycasting problem, a sensor wants to report event information to one
of sinks or actors. We describe the first localized anycasting algorithms that
guarantee delivery for connected multi-sink sensor-actor networks.

Let S(x) be the closest actor/sink to sensor x, and |xS(x)| be distance
between them. In greedy phase, a node s forwards the packet to its neighbor
v that minimizes the ratio of cost cost(|sv|) of sending packet to v (here we
specifically apply hop-count and power consumption metrics) over the
reduction in distance (|sS(s)|−|vS(v)|) to the closest actor/sink.

A variant is to forward to the first neighbor on the shortest weighted path
toward v. If none of neighbors reduces that distance then recovery mode is
invoked.

It is done by face traversal toward the nearest connected actor/sink, where
edges are replaced by paths optimizing given cost. A hop count based and
two variants of localized power aware anycasting algorithms are described.
We prove guaranteed delivery property analytically and experimentally

IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. ?, NO. ?, 1

HIERARCHICAL BAYESIAN SPARSE IMAGE
RECONSTRUCTION WITH APPLICATION TO MRFM

This paper presents a hierarchical Bayesian model to reconstruct sparse
images when the observations are obtained from linear transformations and
corrupted by an additive white Gaussian noise.
Our hierarchical Bayes model is well suited to such naturally sparse image
applications as it seamlessly accounts for properties such as sparsity and
positivity of the image via appropriate Bayes priors.
We propose a prior that is based on a weighted mixture of a positive
exponential distribution and a mass at zero. The prior has hyperparameters
that are tuned automatically by marginalization over the hierarchical
Bayesian model. To overcome the complexity of the posterior distribution, a
Gibbs sampling strategy is proposed.
The Gibbs samples can be used to estimate the image to be recovered, e.g.
by maximizing the estimated posterior distribution. In our fully Bayesian
approach the posteriors of all the parameters are available. Thus our
algorithm provides more information than other previously proposed sparse
reconstruction methods that only give a point estimate.
The performance of the proposed hierarchical Bayesian sparse
reconstruction method is illustrated on synthetic data and real data collected
from a tobacco virus sample using a prototype MRFM instrument.

Index Terms
Deconvolution, MRFM imaging, sparse representation, Bayesian inference,
MCMC methods

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE
INTELLIGENCE, VOL. 31, NO. 2, FEBRUARY 2009

OFFLINE LOOP INVESTIGATION FOR
HANDWRITING ANALYSIS

Study of Rough Set and Clustering Algorithm in Network Security
Management Getting a better grasp of computer network security is of great
significance to protect the normal operation of network system.
Based on rough set (RS), clustering model, security features reduction and
clustering algorithm are presented, which provides a basis of network
security strategies. Further research is to mine and process the dynamic
risks and management of network security.
Using the reduction methods, the simplified network security assessment
data set is established. The extraction by the decision-making rules is
proposed and verified.
Through the results, it is concluded that the method could be in line with the
actual situation of decision-making rules.

Keywords
RS, clustering algorighm, network security, K-W method

VOL. 8, NO. 5, MAY 2009 1

HIGH PERFORMANCE COOPERATIVE
TRANSMISSION PROTOCOLS BASED ON
MULTIUSER DETECTION AND NETWORK CODING

Cooperative transmission is an emerging communication technique that
takes advantage of the broadcast nature of wireless channels. However, due
to low spectral efficiency and the requirement of orthogonal channels, its
potential for use in future wireless networks is limited.
In this paper, by making use of multiuser detection (MUD) and network
coding, cooperative transmission protocols with high spectral efficiency,
diversity order, and coding gain are developed. Compared with the traditional
cooperative transmission protocols with singleuser detection, in which the
diversity gain is only for one source user, the proposed MUD cooperative
transmission protocols have the merit that the improvement of one user’s
link can also benefit the other users.
In addition, using MUD at the relay provides an environment in which
network coding can be employed. The coding gain and high diversity order
can be obtained by fully utilizing the link between the relay and the
destination.
From the analysis and simulation results, it is seen that the proposed
protocols achieve higher diversity gain, better asymptotic efficiency, and
lower bit error rate, compared to traditional MUD schemes and to existing
cooperative transmission protocols.
From the simulation results, the performance of the proposed scheme is near
optimal as the performance gap is 0.12dB for average bit error rate (BER) 10
−6 and 1.04dB for average BER 10 −3, compared to two performance upper
bounds.

Index Terms
Detection, coding, communication networks, and cooperative systems.


NOVEL PACKET-LEVEL RESOURCE ALLOCATION
WITH EFFECTIVE QOS PROVISIONING FOR
WIRELESS MESH NETWORKS

Joint power-subcarrier-time resource allocation is imperative for wireless
mesh networks due to the necessity of packet scheduling for quality-of-
service (QoS) provisioning, multi-channel communications, and
opportunistic power allocation.
In this work, we propose an efficient intra-cluster packet-level resource
allocation approach. Our approach takes power allocation, subcarrier
allocation, packet scheduling, and QoS support into account.
The proposed approach combines the merits of a Karush-Kuhn-Tucker (KKT)-
driven approach and a genetic algorithm (GA)-based approach. It is shown to
achieve a desired balance between time complexity and system performance.
Bounds for the throughputs obtained by real-time and non-real-time traffic
are also derived analytically.

Index Terms—Genetic algorithm (GA), Karush-Kuhn-Tucker (KKT), quality-of-
service (QoS) provisioning, resource allocation, wireless mesh network
(WMN).


MULTI-SERVICE LOAD SHARING FOR
RESOURCE MANAGEMENT IN THE
CELLULAR/WLAN INTEGRATED NETWORK

With the interworking between a cellular network and wireless local area
networks (WLANs), an essential aspect of resource management is taking
advantage of the overlay network structure to efficiently share the multi-
service traffic load between the interworked systems.
In this study, we propose a new load sharing scheme for voice and elastic
data services in a cellular/WLAN integrated network. Admission control and
dynamic vertical handoff are applied to pool the free bandwidths of the two
systems to effectively serve elastic data traffic and improve the multiplexing
gain.
To further combat the cell bandwidth limitation, data calls in the cell are
served under an efficient service discipline, referred to as shortest remaining
processing time (SRPT) [1]. The SRPT can well exploit the heavy-tailedness
of data call size to improve the resource utilization.
An accurate analytical model is developed to determine an appropriate size
threshold so that data calls are properly distributed to the integrated cell and
WLAN, taking into account the load conditions and traffic characteristics. It
is observed from extensive simulation and numerical analysis that the new
scheme significantly improves the overall system performance.

Index Terms
Cellular/WLAN interworking, resource management, quality of service, load
sharing, vertical handoff, admission control.

SOBIE:A NOVEL SUPER-NODE P2P OVERLAY
BASED ON INFORMATION EXCHANGE

In order to guarantee both the efficiency and robustness in the Peer-to-Peer
(P2P) network, the paper designs a novel Super-node Overlay Based on
Information Exchange called SOBIE.
Differing from current structured and unstructured, or meshed and tree-like
P2P overlay, the SOBIE is a whole new structure to improve the efficiency of
searching in the P2P network.
The main contributions are
1) to select the super-nodes by considering the aggregation of not only
the delay, distance, but also the information exchange frequency,
exchange time and query similarity especially;
2) to set a score mechanism to identify and prevent the free-riders.
Meanwhile, the SOBIE also guarantees the matching between the
physical network and logical network and has small-world
characteristic to improve the efficiency.
Large number of experiment results show the advantages of the SOBIE
including high efficiency and robustness by such different factors as the
query success rate, the average query hops, the total number of query
messages, the coverage rate and system connectivity.

Index Terms
P2P overlay, super node, information exchange, topology matching, free-
ridding

AD HOC NETWORKS (ELSEVIER), VOL. 7, NO. 5, PP. 862-881, JULY 2009

OPTIMAL BACKPRESSURE ROUTING FOR WIRELESS
NETWORKS WITH MULTI-RECEIVER DIVERSITY

We consider the problem of optimal scheduling and routing in an ad-hoc
wireless network with multiple traffic streams and time varying channel
reliability.
Each packet transmission can be overheard by a subset of receiver nodes,
with a transmission success probability that may vary from receiver to
receiver and may also vary with time.
We develop a simple backpressure routing algorithm that maximizes network
throughput and expends an average power that can be pushed arbitrarily
close to the minimum average power required for network stability, with a
corresponding tradeoff in network delay.
When channels are orthogonal, the algorithm can be implemented in a
distributed manner using only local link error probability information, and
supports a “blind transmission” mode (where error probabilities are not
required) in special cases when the power metric is neglected and when
there is only a single destination for all traffic streams.
For networks with general inter-channel interference, we present a
distributed algorithm with constant-factor optimality guarantees.

Index Terms
Broadcast advantage, distributed algorithms, dynamic control, mobility,
queueing analysis, scheduling


RANDOMCAST: AN ENERGY-EFFICIENT
COMMUNICATION SCHEME FOR MOBILE AD HOC
NETWORKS

In mobile ad hoc networks (MANETs), every node overhears every data
transmission occurring in its vicinity and thus, consumes energy
unnecessarily. In IEEE 802.11 Power Saving Mechanism (PSM), a packet must
be advertised before it is actually transmitted.
When a node receives an advertised packet that is not destined to itself, it
switches to a low-power sleep state during the data transmission period, and
thus, avoids overhearing and conserves energy.
However, since some MANET routing protocols such as Dynamic Source
Routing (DSR) collect route information via overhearing, they would suffer if
they are used in combination with 802.11 PSM.
Allowing no overhearing may critically deteriorate the performance of the
underlying routing protocol, while unconditional overhearing may offset the
advantage of using PSM. This paper proposes a new communication
mechanism, called RandomCast, via which a sender can specify the desired
level of overhearing, making a prudent balance between energy and routing
performance.
In addition, it reduces redundant rebroadcasts for a broadcast packet, and
thus, saves more energy. Extensive simulation using ns-2 shows that
RandomCast is highly energy-efficient compared to conventional 802.11 as
well as 802.11 PSM-based schemes, in terms of total energy consumption,
energy goodput, and energy balance.

Index Terms
Energy balance, energy efficiency, mobile ad hoc networks, network lifetime,
overhearing, power saving mechanism.

IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. 18, NO. 6, JUNE 2009

ADAPTIVE FUZZY FILTERING FOR ARTIFACT
REDUCTION IN COMPRESSED IMAGES AND
VIDEOS

A fuzzy filter adaptive to both sample’s activity and the relative
position between samples is proposed to reduce the artifacts in
compressed multidimensional signals.
For JPEG images, the fuzzy spatial filter is based on the
directional characteristics of ringing artifacts along the strong
edges.
For compressed video sequences, the motion compensated
spatiotemporal filter (MCSTF) is applied to intraframe and
interframe pixels to deal with both spatial and temporal artifacts.
A new metric which considers the tracking characteristic of human
eyes is proposed to evaluate the flickering artifacts. Simulations
on compressed images and videos show improvement in artifact
reduction of the proposed adaptive fuzzy filter over other
conventional spatial or temporal filtering approaches.

Index Terms
Artifact reduction, flickering metric, fuzzy filter, motion
compensated spatio-temporal filter.

Computer Science and Network Security, VOL.9 No.4, April 2009

A NEW RELIABLE BROADCASTING IN MOBILE
AD HOC NETWORKS

A New Reliable Broadcasting Algorithm for mobile ad hoc networks will
guarantee to deliver the messages from different sources to all the
nodes of the network.
The nodes are mobile and can move from one place to another. The
solution does not require the nodes to know the network size, its
diameter and number of nodes in the network.
The only information a node has its identity (IP Address) and its
position. On average, only a subset of nodes transmits and they
transmit only once to achieve reliable broadcasting.
The algorithm will calculate the relative position of the nodes with
respect to the broadcasting source node. The nodes that are farthest
from the source node will rebroadcast and this will minimize the
number of rebroadcasts made by the intermediate nodes and will
reduce the delay latency.
The proposed algorithm will adapt itself dynamically to the number of
concurrent broadcasts and will give the least finish time for any
particular broadcast. It will be contention free, energy efficient and
collision free.

Key words
Broadcasting Algorithm, IP Address, Mobile Ad Hoc Networks,
Collision, Delay latency.

IEEE COMPUTER ARCHITECTURE LETTERS
VOL. 8, NO. 1, JANUARY-JUNE 2009

AN XML-BASED ADL FRAMEWORK FOR
AUTOMATIC GENERATION OF MULTITHREADED
COMPUTER ARCHITECTURE SIMULATORS

Computer architecture simulation has always played a pivotal role in
continuous innovation of computers. However, constructing or
modifying a high quality simulator is time consuming and error-prone.

Thus, often Architecture Description Languages (ADLs) are used to
provide an abstraction layer for describing the computer architecture
and automatically generating corresponding simulators. Along the line
of such research, we present a novel XML-based ADL, its compiler, and
a generation methodology to automatically generate multithreaded
simulators for computer architecture.

We utilize the industry-standard extensible markup language XML to
describe the functionality and architecture of a modeled processor. Our
ADL framework allows users to easily and quickly modify the structure,
register set, and execution of a modeled processor.

To prove its validity, we have generated several multithreaded
simulators with different configurations based on the MIPS five-stage
processor, and successfully tested with two programs.

CLONE DETECTION AND REMOVAL FOR
ERLANG/OTP WITHIN A REFACTORING
ENVIRONMENT

A well-known bad code smell in refactoring and software maintenance is
duplicated code, or code clones. A code clone is a code fragment that is
identical or similar to another.

Unjustified code clones increase code size, make maintenance and
comprehension more difficult, and also indicate design problems such as
lack of encapsulation or abstraction.

This paper proposes a token and AST based hybrid approach to
automatically detecting code clones in Erlang/OTP programs, underlying a
collection of refactorings to support user-controlled automatic clone
removal, and examines their application in substantial case studies.

Both the clone detector and the refactorings are integrated within Wrangler,
the refactoring tool developed at Kent for Erlang/OTP

Keywords

Erlang, refactoring, Wrangler, duplicated code, program analysis, program
transformation.

IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
VOL. 21, NO. 1, JANUARY 2009

A RELATION-BASED PAGE RANK ALGORITHM FOR
SEMANTIC WEB SEARCH ENGINES

With the tremendous growth of information available to end users through
the Web, search engines come to play ever a more critical role. Nevertheless,
because of their general-purpose approach, it is always less uncommon that
obtained result sets provide a burden of useless pages.
The next-generation Web architecture, represented by the Semantic Web,
provides the layered architecture possibly allowing overcoming this
limitation. Several search engines have been proposed, which allow
increasing information retrieval accuracy by exploiting a key content of
Semantic Web resources, that is, relations.
However, in order to rank results, most of the existing solutions need to work
on the whole annotated knowledge base. In this paper, we propose a relation-
based page rank algorithm to be used in conjunction with Semantic Web
search engines that simply relies on information that could be extracted from
user queries and on annotated resources.
Relevance is measured as the probability that a retrieved resource actually
contains those relations whose existence was assumed by the user at the
time of query definition.

Index Terms
Semantic Web, knowledge retrieval, search process, query formulation.


DYNAMICS OF MULTIPLE-SELLER AND MULTIPLE-
BUYER SPECTRUM TRADING IN COGNITIVE RADIO
NETWORKS: A GAME-THEORETIC MODELING
APPROACH

We consider the problem of spectrum trading with multiple licensed users
(i.e., primary users) selling spectrum opportunities to multiple unlicensed
users (i.e., secondary users). The secondary users can adapt the spectrum
buying behavior (i.e., evolve) by observing the variations in price and quality
of spectrum offered by the different primary users or primary service
providers.
The primary users or primary service providers can adjust their behavior in
selling the spectrum opportunities to secondary users to achieve the highest
utility. In this paper, we model the evolution and the dynamic behavior of
secondary users using the theory of evolutionary game. An algorithm for the
implementation of the evolution process of a secondary user is also
presented.
To model the competition among the primary users, a noncooperative game
is formulated where the Nash equilibrium is considered as the solution (in
terms of size of offered spectrum to the secondary users and spectrum
price). For a primary user, an iterative algorithm for strategy adaptation to
achieve the solution is presented.
The proposed game-theoretic framework for modeling the interactions
among multiple primary users (or service providers) and multiple secondary
users is used to investigate network dynamics under different system
parameter settings and under system perturbation.

Index Terms
Cognitive radio, dynamic spectrum sharing, spectrum trading, Nash
equilibrium, evolutionary equilibrium, replicator dynamics.

IEEE/ACM TRANSACTIONS ON NETWORKING, VOL. 17, NO. 3, JUNE 2009

ENERGY–ROBUSTNESS TRADEOFF IN CELLULAR
NETWORK POWER CONTROL

In the seminal paper by Foschini and Miljanic in 1993, a distributed
power control algorithm was developed to meet SIR targets with
minimal powers in cellular network uplinks. Since the SIR on an active
link may dip below the SIR target during the transient after a new user
enters the cell, Bambos et al. proposed an active link protection
algorithm to provide robustness, at the expense of higher energy
consumption.

This paper examines the tradeoff between energy and robustness. An
optimization problem is formulated where robustness is captured in the
constraint and the price of robustness penalized in the objective
function.

A distributed algorithm is developed to solve this problem. Local
convergence and optimality of equilibrium are proved for the algorithm.
The objective function modulates the tradeoff between energy and
robustness, and between energy and speed of admission, as illustrated
through a series of numerical experiments.

A parameterized family of objective functions is constructed to control
the transient and equilibrium properties of robust distributed power
control.

Index Terms—Distributed optimization, duality, power control, wireless
networks.

TEXTURE IMAGE SEGMENTATION USING
SPECTRAL HISTOGRAM AND SKELETON
EXTRACTING, FEB. 2009

This paper presents a texture image segmentation algorithm
using spectral histogram and skeleton extracting. No need of
selecting seed pixels or specifying or deciding the number of
regions is its remarkable characteristic.

Based on a local spatial/frequency representation, spectral
histogram consists of marginal distributions of responses of a
bank of filters and encodes implicitly the local structure of
images through the filtering stage and the global appearance
through the histogram stage.

The similarity between two spectral histograms is measured
using chi2-statistic. According to the similarity among
spectral histograms, the initial binary segmentation image can
be obtained.

Adopting skeleton extracting algorithm based on
mathematical morphology, the final segmentation result can
be obtained. Experiments on Brodatz textures give
satisfactory results.

AGENT MINING: THE SYNERGY OF AGENTS AND
DATA MINING," IEEE INTELLIGENT SYSTEMS, 2009

Autonomous agents and multiagent systems (or agents) and data mining and
knowledge discovery (or data mining) are two of the most active areas in
information technology. Ongoing research has revealed a number of intrinsic
challenges and problems facing each area, which can't be addressed solely
within the confines of the respective discipline.

A profound insight of bringing these two communities together has unveiled
a tremendous potential for new opportunities and wider applications through
the synergy of agents and data mining.

With increasing interest in this synergy, agent mining is emerging as a new
research field studying the interaction and integration of agents and data
mining. In this paper, we give an overall perspective of the driving forces,
theoretical underpinnings, main research issues, and application domains of
this field, while addressing the state-of-the-art of agent mining research and
development.

Our review is divided into three key research topics: agent-driven data
mining, data mining-driven agents, and joint issues in the synergy of agents
and data mining.

This new and promising field exhibits a great potential for groundbreaking
work from foundational, technological and practical perspectives

Index Terms:

artificial intelligence, autonomous agents, multi-agent systems, knowledge
discovery, data mining

A RELATION-BASED PAGE RANK ALGORITHM FOR
SEMANTIC WEB SEARCH ENGINES

IEEE Transactions on Knowledge and Data Engineering, 2009

With the tremendous growth of information available to end users
through the Web, search engines come to play ever a more critical
role. Nevertheless, because of their general purpose approach, it
is always less uncommon that obtained result sets provide a
burden of useless pages.
Next generation Web architecture, represented by Semantic Web,
provides the layered architecture possibly allowing to overcome
this limitation. Several search engines have been proposed, which
allow to increase information retrieval accuracy by exploiting a
key content of Semantic Web resources, that is relations.
However, in order to rank results, most of the existing solutions
need to work on the whole annotated knowledge base. In this
paper we propose a relation-based page rank algorithm to be used
in conjunction with Semantic Web search engines that simply
relies on information which could be extracted from user query
and annotated resource.
Relevance is measured as the probability that retrieved resource
actually contains those relations whose existence was assumed
by the user at the time of query definition

Index Terms:
Intelligent Web Services and Semantic Web, Knowledge retrieval,
Search process, Query formulation

AN IMPLEMENTATION OF THE BLOWFISH
CRYPTOSYSTEM, 2009

The Blowfish cryptosystem is a very fast and useful scheme, even
though it was introduced over a decade ago. This cryptosystem
consists of two parts, a subkey and S-box generation phase, and
an encrypiton phase.

A short introduction to both algorithms are given, along with a few
notes about the Ciphertext Block Chaining (CBC) mode.

Some general information about attacks are explained, along with
information about some of the people who have worked to analyze
and attempt to break Blowfish. An implementation of a Windows
tool for encrypting files which uses Blowfish is also examined in
this paper.

The results of the encryption tool clearly demonstrate how fast the
encryption is compared to the subkey and S-box generation. The
secrecy of the cryptosystem is explained by using several test
files of different types, as well as a study of the security with
respect to the number of rounds.

Finally, some possible extensions to the software tool to improve
its usefulness based on the strength of Blowfish are given.

SSL/TLS WITH QUANTUM CRYPTOGRAPHY,
FEB. 2009

The current standard to exchange a secret key for
ensuring secure data transmission within the SSL/TLS
protocol is based on Public-Key encryption.

This method is only secure as long as the computation
power of a potential attacker is limited.

So far, the only way to make an unconditional secure key
exchange, is to use quantum key distribution (QKD). With
the latest figures of sifting key rates provided by NIST, we
show which authentic theoretical final key rates are
possible.

Furthermore we present a modified SSL/TLS protocol,
which uses quantum key distribution, in different
encryption variants.

IMAGE TRANSFORMATIONS AND BLURRING

Pattern Analysis and Machine Intelligence, IEEE Transactions on
Volume 31, Issue 5, May 2009

Since cameras blur the incoming light during measurement,
different images of the same surface do not contain the same
information about that surface. Thus, in general, corresponding
points in multiple views of a scene have different image
intensities.
While multiple-view geometry constrains the locations of
corresponding points, it does not give relationships between the
signals at corresponding locations. This paper offers an
elementary treatment of these relationships.
We first develop the notion of "idealrdquo and "realrdquo images,
corresponding to, respectively, the raw incoming light and the
measured signal. This framework separates the filtering and
geometric aspects of imaging.
We then consider how to synthesize one view of a surface from
another; if the transformation between the two views is affine, it
emerges that this is possible if and only if the singular values of
the affine matrix are positive.
Next, we consider how to combine the information in several views
of a surface into a single output image. By developing a new tool
called "frequency segmentation," we show how this can be done
despite not knowing the blurring kernel.

AUTOMATIC ASCII ART CONVERSION OF BINARY
IMAGES USING NON-NEGATIVE CONSTRAINTS

It is hard to avoid ASCII Art in today's digital world, from the
ubiquitous emoticons—;)—to the esoteric artistic creations
that reside in many people's e-mail signatures, everybody has
come across ASCII art at some stage.

The origins of ASCII art can be traced back to the days when
computers had a high price, slow operating speeds and low
graphics capabilities, which forced computer programmers
and enthusiasts to develop some innovative ways to render
images using the limited graphics blocks available, viz., text
characters.

Here, we treat automatic ASCII art conversion of binary
images as an optimisation problem, and present an
application of our work on Non-Negative Matrix Factorisation
to this task—where a basis constructed from monospace font
glyphs is fitted to a binary image using a winner-takes-all
assignment.

DATA-MINING-ENHANCED AGENTS IN DYNAMIC
SUPPLY-CHAIN-MANAGEMENT ENVIRONMENTS
IEEE Intelligent Systems, May/June 2009

In modern supply chains, stakeholders with varying degrees of
autonomy and intelligence compete against each other in a
constant effort to establish beneficiary contracts and maximize
their own revenue.
In such competitive environments, entities—software agents being
a typical programming paradigm—interact in a dynamic and
versatile manner, so each action can cause ripple reactions and
affect the overall result.
In this article, the authors argue that the utilization of data mining
primitives could prove beneficial in order to analyze the supply-
chain model and identify pivotal factors.
They elaborate on the benefits of data mining analysis on a well-
established agent supply-chain management network, both at a
macro and micro level. They also analyze the results and discuss
specific design choices in the context of agent performance
improvement.

Index Terms:
intelligent agents, data mining, supply chain management,
auctions, bidding

FUZZY CONTROL MODEL OPTIMIZATION FOR
BEHAVIOR-CONSISTENT TRAFFIC ROUTING
UNDER INFORMATION PROVISION

IEEE Transactions on 2009

This paper presents an H-infinity filtering approach to optimize a fuzzy
control model used to determine behavior-consistent (BC) information-
based control strategies to improve the performance of congested
dynamic traffic networks.

By adjusting the associated membership function parameters to better
respond to nonlinearities and modeling errors, the approach is able to
enhance the computational performance of the fuzzy control model.
Computational efficiency is an important aspect in this problem
context, because the information strategies are required in subreal time
to be real-time deployable.

Experiments are performed to evaluate the effectiveness of the
approach. The results indicate that the optimized fuzzy control model
contributes in determining the BC information-based control strategies
in significantly less computational time than when the default controller
is used.

Hence, the proposed H-infinity approach contributes to the
development of an efficient and robust information-based control
approach.

IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS
VOL. 18, NO. 7, JULY 2007

AN SSL BACK-END FORWARDING SCHEME IN
CLUSTER-BASED WEB SERVERS

State-of-the-art cluster-based data centers consisting of three tiers (Web
server, application server, and database server) are being used to host
complex Web services such as e-commerce applications. The application
server handles dynamic and sensitive Web contents that need protection
from eavesdropping, tampering, and forgery.
Although the Secure Sockets Layer (SSL) is the most popular protocol to
provide a secure channel between a client and a cluster-based network
server, its high overhead degrades the server performance considerably and,
thus, affects the server scalability.
Therefore, improving the performance of SSL-enabled network servers is
critical for designing scalable and high-performance data centers. In this
paper, we examine the impact of SSL offering and SSL-session-aware
distribution in cluster-based network servers.
We propose a back-end forwarding scheme, called ssl_with_bf, that employs
a low-overhead user-level communication mechanism like Virtual Interface
Architecture (VIA) to achieve a good load balance among server nodes. We
compare three distribution models for network servers, Round Robin (RR),
ssl_with_session, and ssl_with_bf, through simulation.
The experimental results with 16-node and 32-node cluster configurations
show that, although the session reuse of ssl_with_session is critical to
improve the performance of application servers, the proposed back-end
forwarding scheme can further enhance the performance due to better load
balancing.
The ssl_with_bf scheme can minimize the average latency by about 40
percent and improve throughput across a variety of workloads.

Index Terms
Secure Sockets Layer, cluster, Web servers, application server layer, load
distribution, user-level communication.

IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
VOL. 19, NO. 7, JULY 2007

EFFICIENT APPROXIMATE QUERY PROCESSING IN
PEER-TO-PEER NETWORKS

Peer-to-peer (P2P) databases are becoming prevalent on the Internet for
distribution and sharing of documents, applications, and other digital media.
The problem of answering large-scale ad hoc analysis queries, for example,
aggregation queries, on these databases poses unique challenges. Exact
solutions can be time consuming and difficult to implement, given the
distributed and dynamic nature of P2P databases.
In this paper, we present novel sampling-based techniques for approximate
answering of ad hoc aggregation queries in such databases. Computing a
high-quality random sample of the database efficiently in the P2P
environment is complicated due to several factors: the data is distributed
(usually in uneven quantities) across many peers, within each peer, the data
is often highly correlated, and, moreover, even collecting a random sample of
the peers is difficult to accomplish.
To counter these problems, we have developed an adaptive two-phase
sampling approach based on random walks of the P2P graph, as well as
block-level sampling techniques. We present extensive experimental
evaluations to demonstrate the feasibility of our proposed solution.

Index Terms
Approximation methods, computer networks, distributed databases,
distributed database query processing, distributed estimation, database
systems, distributed systems.

SECURE ELECTRONIC DATA INTERCHANGE OVER
THE INTERNET - 2005

Numerous retailers, manufacturers, and other companies within business
supply chains are leveraging Applicability Statement #2 (AS2) and other
standards developed by the IETF’s Electronic Data Interchange over the
Internet (EDI-INT) working group (www. imc.org/ietf-ediint/).

Founded in 1996 to develop a secure transport service for EDI business
documents, the EDI-INT WG later expanded its focus to include XML and
virtually any other electronic business-documentation format.

It began by providing the digital security and message-receipt validation for
Internet communication for MIME (Multipurpose Internet Mail Extensions)
packaging of EDI.1 EDI-INT has since become the leading means of business-
to-business (B2B) transport for retail and other industries. Although invisible
to the consumer, standards for secure electronic communication of purchase
orders, invoices, and other business transactions are helping enterprises
drive down costs and offer flexibility in B2B relationships.

EDI-INT provides digital security of email, Web, and FTP payloads through
authentication, content-integrity, confidentiality, and receipt validation.

BENEFIT-BASED DATA CACHING IN AD HOC NETWORTS

Data caching can significantly improve the efficiency of information access
in a wireless ad hoc network by reducing the access latency and bandwidth
usage.

However, designing efficient distributed caching algorithms is non-trivial
when network nodes have limited memory. In this article, we consider the
cache placement problem of minimizing total data access cost in ad hoc
networks with multiple data items and nodes with limited memory capacity.
The above optimization problem is known to be NP-hard.

Defining benefit as the reduction in total access cost, we present a
polynomial-time centralized approximation algorithm that provably delivers a
solution whose benefit is at least one-fourth (one-half for uniform-size data
items) of the optimal benefit.

The approximation algorithm is amenable to localized distributed
implementation, which is shown via simulations to perform close to the
approximation algorithm. Our distributed algorithm naturally extends to
networks with mobile nodes.

We simulate our distributed algorithm using a network simulator (ns2), and
demonstrate that it significantly outperforms another existing caching
technique (by Yin and Cao [30]) in all important performance metrics.

The performance differential is particularly large in more challenging
scenarios, such as higher access frequency and smaller memory

ON THE COMPUTATIONAL COMPLEXITY AND
EFFECTIVENESS OF N-HUB SHORTEST-PATH ROUTING

In this paper we study the computational complexity and
effectiveness of a concept we term ?N-hub Shortest- Path
Routing? in IP networks.
N-hub Shortest-Path Routing allows the ingress node of a routing
domain to determine up to N intermediate nodes (?hubs?) through
which a packet will pass before reaching its final destination.
This facilitates better utilization of the network resources, while
allowing the network routers to continue to employ the simple and
well-known shortest-path routing paradigm. Although this concept
has been proposed in the past, this paper is the rst to investigate
it in depth.
We apply N-hub Shortest-Path Routing to the problem of
minimizing the maximum load in the network. We show that the
resulting routing problem is NP-complete and hard to
approximate.
However, we propose efficient algorithms for solving it both in the
online and the offline contexts. Our results show that N-hub
Shortest-Path Routing can increase network utilization
significantly even for ??.
Hence, this routing paradigm should be considered as a powerful
mechanism for future datagram routing in the Internet

IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS
VOL. 18, NO. 6, JUNE 2007

PFUSION: A P2P ARCHITECTURE FOR INTERNET-
SCALE CONTENT-BASED SEARCH AND RETRIEVAL

The emerging Peer-to-Peer (P2P) model has become a very powerful and
attractive paradigm for developing Internet-scale systems for sharing
resources, including files and documents.
The distributed nature of these systems, where nodes are typically located
across different networks and domains, inherently hinders the efficient
retrieval of information.
In this paper, we consider the effects of topologically aware overlay
construction techniques on efficient P2P keyword search algorithms. We
present the Peer Fusion (pFusion) architecture that aims to efficiently
integrate heterogeneous information that is geographically scattered on
peers of different networks. Our approach builds on work in unstructured
P2P systems and uses only local knowledge.
Our empirical results, using the pFusion middleware architecture and data
sets from Akamai’s Internet mapping infrastructure (AKAMAI), the Active
Measurement Project (NLANR), and the Text REtrieval Conference (TREC)
show that the architecture we propose is both efficient and practical.

Index Terms
Information retrieval, peer-to-peer, overlay construction algorithm

A SOFTWARE DEFECT REPORT AND TRACKING
SYSTEM IN AN INTRANET

This paper describes a case study where SofTrack - a
Software Defect Report and Tracking System – was
implemented using internet technology in a geographically
distributed organization.

Four medium to large size information systems with different
levels of maturity are being analyzed within the scope of this
project. They belong to the Portuguese Navy’s Information
Systems Infrastructure and were developed using typical
legacy systems technology: COBOL with embedded SQL for
queries in a Relational Database environment.

This pilot project of Empirical Software Engineering has
allowed the development of techniques to help software
managers to better understand, control and ultimately
improve the software process.

Among them are the introduction of automatic system
documentation, module’s complexity assessment and effort
estimation for maintenance activities in the organization

MULTIPLE ANT COLONIES
OPTIMIZATION FOR LOAD BALANCING
IN DISTRIBUTED SYSTEMS

Ant colony optimization (ACO) has proved its success as a
meta-heuristic optimization in several network applications
such as routing and load balancing. In this paper, a proposed
ACO algorithm for load balancing in distributed systems will
be presented.
This algorithm is fully distributed in which information is
dynamically updated at each ant movement. Multiple colonies
paradigm will be adopted such that each node will send a
colored colony throughout the network.
Using colored ant colony helps in preventing ants of the same
nest from following the same route, and hence enforcing them
to be distributed all over the nodes in the network.
Each ant acts like a mobile agent that carries newly updated
load balancing information to the next visited node. Finally,
the proposed algorithm will be compared with the standard
work-stealing algorithm

IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, VOL. 16,
NO. 9, SEPTEMBER 2004

WORKFLOW MINING: DISCOVERING PROCESS
MODELS FROM EVENT LOGS

Contemporary workflow management systems are driven by explicit
process models, i.e., a completely specified workflow design is
required in order to enact a given workflow process.
Creating a workflow design is a complicated time-consuming process
and, typically, there are discrepancies between the actual workflow
processes and the processes as perceived by the management.
Therefore, we have developed techniques for discovering workflow
models. The starting point for such techniques is a so-called “workflow
log” containing information about the workflow process as it is actually
being executed.
We present a new algorithm to extract a process model from such a log
and represent it in terms of a Petri net. However, we will also
demonstrate that it is not possible to discover arbitrary workflow
processes.
In this paper, we explore a class of workflow processes that can be
discovered. We show that the algorithm can successfully mine any
workflow represented by a so-called SWF-net.

Index Terms
Workflow mining, workflow management, data mining, Petri nets

DISTRIBUTED DATA MINING IN CREDIT CARD FRAUD
DETECTION CREDIT CARD TRANSACTIONS CONTINUE

To grow in number, taking an ever-larger share of the US payment
system and leading to a higher rate of stolen account numbers and
subsequent losses by banks. Improved fraud detection thus has
become essential to maintain the viability of the US payment system.

Banks have used early fraud warning systems for some years. Large-
scale data-mining techniques can improve on the state of the art in
commercial practice. Scalable techniques to analyze massive amounts
of transaction data that efficiently compute fraud detectors in a timely
manner is an important problem, especially for e-commerce.

Besides scalability and efficiency, the fraud-detection task exhibits
technical problems that include skewed distributions of training data
and nonuniform cost per error, both of which have not been widely
studied in the knowledge-discovery and datamining community.

In this article, we survey and evaluate a number of techniques that
address these three main issues concurrently. Our proposed methods
of combining multiple learned fraud detectors under a “cost model” are
general and demonstrably useful; our empirical results demonstrate
that we can significantly reduce loss due to fraud through distributed
data mining of fraud models.

QUANTUM CRYPTOGRAPHIC KEY
DISTRIBUTION PROTOCOLS

The application of the principles of quantum mechanics to
cryptography has led to a respectable new dimension in
confidential communication.
As a result of these developments, it is now possible to
construct cryptographic communication systems which detect
unauthorized eavesdropping should it occur, and which give a
incontestable guarantee of no eavesdropping should it not
occur.
Here several protocols for such communication systems are
explored. We first examine quantum bit commitment protocols
which are proven as not being unconditionally secure, then,
we take a look at proposed protocols which are constructed to
disprove the proofs claiming that unconditionally secure
quantum bit commitment protocols are impossible.

Keywords: Quantum Cryptography, Key distribution, Protocol

SCHEMA CONVERSION FROM RELATION TO XML
WITH SEMANTIC CONSTRAINTS

This paper studies the schema conversion from relational
schemas to XML DTDs.
As functional dependencies play an important role in
schema conversion process, the concept of functional
dependency for XML DTDs is proposed to preserve the
semantics implied by functional dependencies and keys of
relational schemas.
A conversion method called NeT-FD (Nesting- Based
Translation with Functional Dependencies) is proposed to
convert relational schemas to XML DTDs in the presence
of functional dependencies and keys.
The method presented here can preserve the semantics
implied by functional dependencies and keys of relational
schemas and can convert multiple tables to XML DTDs at
the same time.

Java Projects Ieee Projects

More Related Content

Similar to Java Projects Ieee Projects (20)

More from ncct (20)

Recently uploaded (20)

Java Projects Ieee Projects