.Net projects 2011 by core ieeeprojects.com
- 1. Core IEEE Projects (Division of Conceptz) #108,5th Main, 4th Cross, Hanumanth Nagar, Basavanagudi, Bangalore-50, Website: www.coreieeeprojects.com contact: 9535052050 IEEE 2011 Projects List/2011 IEEE Projects Title: A Policy Enforcing Mechanism for Trusted Ad Hoc Networks To ensure fair and secure communication in Mobile Ad hoc Networks (MANETs), the applications running in these networks must be regulated by proper communication policies. However, enforcing policies in MANETs is challenging because they lack the infrastructure and trusted entities encountered in traditional distributed systems. This paper presents the design and implementation of a policy enforcing mechanism based on trusted execution monitor built on top of the Trusted Platform Module. Under this mechanism, each application or protocol has an associated policy. Two instances of an application running on different nodes may engage in communicat ion only if these nodes enforce the same set of policies for both the application and the underlying protocols used by the application. In this way, nodes can form trusted application centric networks. Before allowing a node to join such a network, Satem v erifies its trustworthiness of enforcing the required set of policies. If any of them is compromised, Satem disconnects the node from the network. We demonstrate the correctness of our solution through security analysis, and its low overhead through performance evaluation of the applications. Title: A Query Formulation Language for the data web We present a query formulation language called MashQL in order to easily query and fuse structured data on the web. The main novelty of MashQL is that it allows people with limited IT-skills to explore and query one or multiple data sources without prior knowledge about the schema, structure, vocabulary, or any technical details of these sources. More importantly, to be robust and cover most cases in practice, we do not assume that a data source should have -an offline or inline- schema. This poses several language-design and performance complexities that we fundamentally tackle. To illustrate the query formulation power of MashQL, and without loss of generality, we chose the Data Web scenario. We also chose querying RDF, as it is the most primitive data model; hence, MashQL can be similarly used for querying relational databases and XML. We present two implementations of MashQL, an online mashup editor, and a Firefox add-on. The former illustrates how MashQL can be used to query and mash up the Data Web as simple as filtering and piping web feeds; and the Firefox addon illustrates using the browser as a web composer rather than only a navigator. To end, we evaluate MashQL on querying two datasets, DBLP and DBPedia, and show that our indexing techniques allow instant user -interaction.
- 2. Core IEEE Projects (Division of Conceptz) #108,5th Main, 4th Cross, Hanumanth Nagar, Basavanagudi, Bangalore-50, Website: www.coreieeeprojects.com contact: 9535052050 Title: A Privacy-Preserving Remote Data Integrity Checking Protocol with Data Dynamics and Public Verifiability To ensure fair and secure communication in Mobile Ad hoc Networks (MANETs), the applications running in these networks must be regulated by proper communication policies. However, enforcing policies in MANETs is challenging because they lack the infrastructure and tr usted entities encountered in traditional distributed systems. This paper presents the design and implementation of a policy enforcing mechanism based on trusted execution monitor built on top of the Trusted Platform Module. Under this mechanism, each application or protocol has an associated policy. Two instances of an application running on different nodes may engage in communication only if these nodes enforce the same set of policies for both the application and the underlying protocols used by the application. In this way, nodes can form trusted application centric networks. Before allowing a node to join such a network, Satem verifies its trustworthiness of enforcing the required set of policies. If any of them is compromised, Satem disconnects the node from the network. We demonstrate the correctness of our solution through security analysis, and its low overhead through performance evaluation of the applications. Title: Adaptive Fault Tolerant QoS Control Algorithms for Maximizing Data sensing and retrieval in wireless sensor systems have a widespread application in areas such as security and surveillance monitoring, and command and control in battlefields. In query -based wireless sensor systems, a user would issue a query and expect a response to be returned within the deadline. While the use of fault tolerance mechanisms through redundancy improves query reliability in the presence of unreliable wireless communication and sensor faults, it could cause the energy of the system to be quickly depleted. Therefore, there is an inherent tradeoff between query reliability vs. energy consumption in query - based wireless sensor systems. In this paper, we develop adaptive fault tolerant quality of service (QoS) control algorithms based on hop -by-hop data delivery utilizing “source” and “path” redundancy, with the goal to satisfy application QoS requirements while prolonging the lifetime of the sensor system. We develop a mathematical model for the lifetime of the sensor system as a function of syste m parameters including the “source” and “path” redundancy levels utilized. We discover that there exists optimal “source” and “path” redundancy under which the lifetime of the system is maximized while satisfying application QoS requirements. Numerical data are presented and validated through extensive simulation, with physical interpretations given, to demonstrate the feasibility of our algorithm design.
- 3. Core IEEE Projects (Division of Conceptz) #108,5th Main, 4th Cross, Hanumanth Nagar, Basavanagudi, Bangalore-50, Website: www.coreieeeprojects.com contact: 9535052050 Title: Adaptive Provisioning of Human Expertise in Service-oriented Systems Web-based collaborations have become essential in today’s business environments. Due to the availability of various SOA frameworks, Web services emerged as the de facto technology to realize flexible compositions of services. While most existing work focuses on the discovery a nd composition of software based services, we highlight concepts for a people -centric Web. Knowledge- intensive environments clearly demand for provisioning of human expertise along with sharing of computing resources or business data through software -based services. To address these challenges, we introduce an adaptive approach allowing humans to provide their expertise through services using SOA standards, such as WSDL and SOAP. The seamless integration of humans in the SOA loop triggers numerous social implications, such as evolving expertise and drifting interests of human service providers. Here we propose a framework that is based on interaction monitoring techniques enabling adaptations in SOA -based socio- technical systems. Title: Automated Certification for Compliant Cloud-based Business Processes A key problem in the deployment of large -scale, reliable cloud computing concerns the difficulty to certify the compliance of business processes operating in the cloud. Standard audit procedures such as SAS -70 and SAS- 117 are hard to conduct for cloud based processes. The paper proposes a novel approach to certify the compliance of business processes with regulatory requirements. The approach translates process models into their corresponding Petri net representations and checks them against requiremen ts also expressed in this formalism. Being Based on Petri nets, the approach provides well -founded evidence on adherence and, in case of noncompliance, indicates the possible vulnerabilities. Keywords: Business process models, Cloud computing, Compliance certification, Audit, Petri nets.
- 4. Core IEEE Projects (Division of Conceptz) #108,5th Main, 4th Cross, Hanumanth Nagar, Basavanagudi, Bangalore-50, Website: www.coreieeeprojects.com contact: 9535052050 Title: Data Integrity Proofs in Cloud Storage Cloud computing has been envisioned as the de -facto solution to the rising storage costs of IT Enterprises. With the high costs of data storage devices as well as the rapid rate at which data is being generated it proves costly for enterprises or individual users to frequently update their hardware. Apart from reduction in storage costs data outsourcing to the cloud also helps in reducing the maintenance. Cloud storage moves the user’s data to large data centers, which are remotely located, on which user does not have any control. However, this unique feature of the cloud poses many new security challenges which need to be clearly understood and resolved. We provide a sc heme which gives a proof of data integrity in the cloud which the customer can employ to check the correctness of his data in the cloud. This proof can be agreed upon by both the cloud and the customer and can be incorporated in the Service level agreement (SLA). Title: Data Leakage Detection A data distributor has given sensitive data to a set of supposedly trusted agents (third parties). Some of the data is leaked and found in an unauthorized place (e.g., on the web or somebody’s laptop). The distributor must assess the likelihood that the leaked data came from one or more agents, as opposed to having been independently gathered by other means. We propose data allocation strategies (across the agents) that improve the probability of identifying leakages. These methods do not rely on alterations of the released data (e.g., watermarks). In some cases we can also inject “realistic but fake” data records to further improve our chances of detecting leakage and identifying the guilty party . Title: Efficient Computation of Range Aggregates Against Uncertain Location Based Queries In many applications, including location based services, queries may not be precise. In this paper, we study the problem of efficiently computing range aggregates in a multidimensional space when the query location is uncertain. Specifically, for a query point Q whose location is uncertain and a set S of points in a multi-dimensional space, we want to calculate the aggregate (e.g., count, average and sum) over the subset SI of S, Q has at least probability θ within the distance γ to p. We propose novel, efficient techniques to solve the problem following the filtering-and-verification paradigm. In particular, two novel filtering techniques are proposed to effectively and ef ficiently remove data points from verification. Our comprehensive experiments based on both real and synthetic data demonstrate the efficiency and scalability of our techniques.
- 5. Core IEEE Projects (Division of Conceptz) #108,5th Main, 4th Cross, Hanumanth Nagar, Basavanagudi, Bangalore-50, Website: www.coreieeeprojects.com contact: 9535052050 Title: Enabling Public Auditability and Data Dynamics For Storage Security in Cloud Computing Cloud Computing has been envisioned as the next -generation architecture of IT Enterprise. It moves the application software and databases to the centralized large data centers, where the management of the data and services may not be fully trustworthy. This unique paradigm brings about many new security challenges, which have not been well understood. This work studies the problem of ensuring the integrity of data storage in Cloud Computing. In particular, we consider the task of allowing a third party auditor (TPA), on behalf of the cloud client, to verify the integrity of the dynamic data stored in the cloud. The introduction of TPA eliminates the involvement of the client through the auditing of whether his data stored in the cloud i s indeed intact. The support for data dynamics via the most general forms of data operation, such as block modification, insertion and deletion, is also a significant step toward practicality, since services in Cloud Computing are not limited to archive or backup data only. While prior works on ensuring remote data integrity often lacks the support of either public auditability or dynamic data operations, this paper achieves both. We first identify the difficulties and potential security problems of direct extensions with fully dynamic data updates from prior works and then show how to construct an elegant verification scheme for the seamless integration of these two salient features in our design. In particular, to achieve efficient data dynamics, we improve the existing proof of storage models by manipulating block tag authentication. To support efficient handling of multiple auditing tasks, we further explore the technique of signature to extend our main result into a multi - user setting, where TPA can perform multiple auditing tasks simultaneously. Extensive security and performance analysis show that the proposed schemes are highly efficient and provably secure. Title: Exploiting Dynamic Resource Allocation for Efficient Parallel Data Processing in the Cloud Cloud computing companies have started to integrate frameworks for parallel data processing in their product portfolio, making it easy for customers to access these services and to deploy their programs. However, the processing frameworks which are currently used have been designed for static, homogeneous cluster setups and disregard the particular nature of a cloud. Consequently, the allocated compute resources may be inadequate for big parts of the submitted job and unnecessarily increase processing time and cost. In this paper we discuss the opportunities and challenges for efficient parallel data processing in clouds and present our research project. It is the first data processing framework to explicitly exploit the dynamic resource allocation offered b y today’s IaaS clouds for both, task scheduling and execution. Particular tasks of a processing job can be assigned to different types of virtual machines which are automatically instantiated and terminated during the job execution.
- 6. Core IEEE Projects (Division of Conceptz) #108,5th Main, 4th Cross, Hanumanth Nagar, Basavanagudi, Bangalore-50, Website: www.coreieeeprojects.com contact: 9535052050 Title: Exploring Application-Level Semantics for Data Compression Natural phenomena show that many creatures form large social groups and move in regular patterns. However, previous works focus on finding the movement patterns of each single object or all objects. In this paper, we first propose an efficient distributed mining algorithm to jointly identify a group of moving objects and discover their movement patterns in wireless sensor networks. Afterward, we propose a compression algorithm, called 2P2D, which exploits the obtained group movement patterns to reduce the amount of delivered data. The compression algorithm includes a sequence merge and an entropy reduction phases. In the sequence merge phase, we propose a Merge algorithm to merge and compress the location data of a group of moving objects. In the entropy reduction phase, we formulate a Hit Item Replacement (HIR) problem and propose a Replace algorithm that obtains the optimal solution. Moreover, we devise three replacement rules and derive the maxim um compression ratio. The experimental results show that the proposed compression algorithm leverages the group movement patterns to reduce the amount of delivered data effectively and efficiently. Title: Improving Aggregate Recommendation Diversity Using Ranking-Based Techniques Recommender systems are becoming increasingly important to individual users and businesses for providing personalized recommendations. However, while the majority of algorithms proposed in 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 propos ed techniques using several real-world rating datasets and different rating prediction algorithms.
- 7. Core IEEE Projects (Division of Conceptz) #108,5th Main, 4th Cross, Hanumanth Nagar, Basavanagudi, Bangalore-50, Website: www.coreieeeprojects.com contact: 9535052050 Title: Jamming-Aware Traffic Allocation for Multiple-Path Routing Using Portfolio Selection Multiple-path source routing protocols allow a data source node to distribute the total traffic among available paths. In this article, we consider the problem of jamming-aware source routing in which the source node performs traffic allocation based on empirical jamming statistics at individual network nodes. We formulate this traffic allocation as a lossy network flow optimization problem using portfolio selection theory from financial statistics. We show that in multi-source networks, this centralized optimization problem can be solved using a distributed algorithm based on decomposition in network utility maximization (NUM). We demonstrate the network’s ability to estimate the impact of jamming and incorporate these estimates into the traffic allocation problem. Finally, we simulate the achievable throughput using our proposed traffic allocation method in several scenarios. Title: Live Streaming with Receiver-based Peer-division Multiplexing A number of commercial peer-to-peer systems for live streaming have been introduced in recent years. The behavior of these popular systems has been extensively studied in several measurement papers. Due to the proprietary nature of these commercial systems, however, these studies have to rely on a “black -box” approach, where packet traces are collected from a sing le or a limited number of measurement points, to infer various properties of traffic on the control and data planes. Although such studies are useful to compare different systems from end - user’s perspective, it is difficult to intuitively understand the ob served properties without fully reverse-engineering the underlying systems. In this paper we describe the network architecture of Zattoo, one of the largest production live streaming providers in Europe at the time of writing, and present a large -scale measurement study of Zattoo using data collected by the provider. To highlight, we found that even when the Zattoo system was heavily loaded with as high as 20,000 concurrent users on a single overlay, the median channel join delay remained less than 2 to 5 seconds, and that, for a majority of users, the streamed signal lags over-the-air broadcast signal by no more than 3 seconds. Title: Monitoring Service Systems from a Language-Action Perspective The Exponential growth in the global economy is being sup ported by service systems, realized by recasting mission -critical application services accessed across organizational boundaries. Language-Action Perspective (LAP) is based upon the notion as proposed that "expert behavior requires an exquisite sensitivity to context and that such sensitivity is more in the realm of the human than in that of the artificial.
- 8. Core IEEE Projects (Division of Conceptz) #108,5th Main, 4th Cross, Hanumanth Nagar, Basavanagudi, Bangalore-50, Website: www.coreieeeprojects.com contact: 9535052050 Business processes are increasingly distributed and open, making them prone to failure. Monitoring is, therefore, an important concern not only for the processes themselves but also for the services that comprise these processes. We present a framework for multilevel monitoring of these service systems. It formalizes interaction protocols, policies, and commitments that account for standard and extended effects following the language -action perspective, and allows specification of goals and monitors at vari ed abstraction levels. We demonstrate how the framework can be implemented and evaluate it with multiple scenarios like between merchant and customer transaction that include specifying and monitoring open-service policy commitments. Title: Network Coding Based Privacy Preservation against Traffic Analysis in Multi-hop Wireless Networks Privacy threat is one of the critical issues in multihop wireless networks, where attacks such as traffic analysis and flow tracing can be easi ly launched by a malicious adversary due to the open wireless medium. Network coding has the potential to thwart these attacks since the coding/mixing operation is encouraged at intermediate nodes. However, the simple deployment of network coding cannot achieve the goal once enough packets are collected by the adversaries. On the other hand, the coding/mixing nature precludes the feasibility of employing the existing privacy -preserving techniques, such as Onion Routing. In this paper, we propose a novel net work coding based privacy- preserving scheme against traffic analysis in multichip wireless networks. With homomorphism encryption, the proposed scheme offers two significant privacy - preserving features, packet flow intractability and message content confidentiality, for efficiently thwarting the traffic analysis attacks. Moreover, the proposed scheme keeps the random coding feature. Theoretical analysis and simulative evaluation demonstrate the validity and efficiency of the proposed scheme.
- 9. Core IEEE Projects (Division of Conceptz) #108,5th Main, 4th Cross, Hanumanth Nagar, Basavanagudi, Bangalore-50, Website: www.coreieeeprojects.com contact: 9535052050 Title: One Size Does Not Fit All Towards User- and Query-Dependent Ranking For Web Databases With the emergence of the deep Web, searching Web databases in domains such as vehicles, real estate, etc. has become a routine task. One of the problems in this context is ranking the results of a user query. Earlier approaches for addressing this problem have used frequencies of database values, query logs, and user profiles. A common thread in most of these approaches is that ranking is done in a user- and/or query-independent manner. This paper proposes a novel query- and user-dependent approach for ranking query results in Web databases. We present a ranking model, based on two complementary notions of user and query similarity, to derive a ranking function for a given user query. This fu nction is acquired from a sparse workload comprising of several such ranking functions derived for various user-query pairs. The model is based on the intuition that similar users display comparable ranking preferences over the results of similar queries. We define these similarities formally in alternative ways and discuss their effectiveness analytically and experimentally over two distinct Web databases. Title: Optimal service pricing for a cloud cache Cloud applications that offer data management services are emerging. Such clouds support caching of data in order to provide quality query services. The users can query the cloud data, paying the price for the infrastructure they use. Cloud management necessitates an economy that manages the service o f multiple users in an efficient, but also, resource economic way that allows for cloud profit. Naturally, the maximization of cloud profit given some guarantees for user satisfaction presumes an appropriate price -demand model that enables optimal pricing of query services. The model should be plausible in that it reflects the correlation of cache structures involved in the queries. Optimal pricing is achieved based on a dynamic pricing scheme that adapts to time changes. This paper proposes a novel price-demand model designed for a cloud cache and a dynamic pricing scheme for queries executed in the cloud cache. The pricing solution employs a novel method that estimates the correlations of the cache services in an time-efficient manner. The experimental stu dy shows the efficiency of the solution.
- 10. Core IEEE Projects (Division of Conceptz) #108,5th Main, 4th Cross, Hanumanth Nagar, Basavanagudi, Bangalore-50, Website: www.coreieeeprojects.com contact: 9535052050 Title: Optimal Stochastic Location Updates In Mobile Ad Hoc Networks We consider the location service in a mobile ad -hoc network (MANET), where each node needs to maintain its location information by 1) frequently updating its location information within its neighboring region, which is called neighborhood update (NU), and 2) occasionally updating its location information to certain distributed location server in the network, which is called location server update (LSU). The tradeoff between the operation costs in location updates and the performance losses of the target application due to location inaccuracies (i.e., application costs) imposes a crucial question for nodes to decide the optimal strategy to update their location information, where the optimality is in the sense of minimizing the overall costs. In this paper, we develop a stochastic sequential decision framework to analyze this problem. Under a Markovian mobility model, the location update decision problem is modeled as a Markov Decision Process (MDP). We first investigate the monotonicity properties of optimal NU and LSU operations with respect to location inaccuracies under a general cost setting. Then, given a separable cost structure, we s how that the location update decisions of NU and LSU can be independently carried out without loss of optimality, i.e., a separation property. From the discovered separation property of the problem structure and the monotonicity properties of optimal actio ns, we find that 1) there always exists a simple optimal threshold -based update rule for LSU operations; 2) for NU operations, an optimal threshold -based update rule exists in a low-mobility scenario. In the case that no a priori knowledge of the MDP model is available, we also introduce a practical model -free learning approach to find a near-optimal solution for the problem. Title: Personalized Ontology Model for Web Information Gathering As a model for knowledge description and formalization, ontolo gies are widely used to represent user profiles in personalized web information gathering. However, when representing user profiles, many models have utilized only knowledge from either a global knowledge base or user local information. In this paper, a personalized ontology model is proposed for knowledge representation and reasoning over user profiles. This model learns ontological user profiles from both a world knowledge base and user local instance repositories. The ontology model is evaluated by comparing it against benchmark models in web information gathering. The results show that this ontology model is successful . Title: Privacy-Preserving Updates to Anonymous and Confidential Databases
- 11. Core IEEE Projects (Division of Conceptz) #108,5th Main, 4th Cross, Hanumanth Nagar, Basavanagudi, Bangalore-50, Website: www.coreieeeprojects.com contact: 9535052050 Suppose Alice owns a k-anonymous database and needs to determine whether her database, when inserted with a tuple owned by Bob, is still k -anonymous. Also, suppose that access to the database is strictly controlled, because for example data are used for certain experiments that need to be maintained confidenti al. Clearly, allowing Alice to directly read the contents of the tuple breaks the privacy of Bob (e.g., a patient’s medical record); on the other hand, the confidentiality of the database managed by Alice is violated once Bob has access to the contents of the database. Thus, the problem is to check whether the database inserted with the tuple is still k -anonymous, without letting Alice and Bob know the contents of the tuple and the database respectively. In this paper, we propose two protocols solving this problem on suppression-based and generalization-based k-anonymous and confidential databases. The protocols rely on well-known cryptographic assumptions, and we provide theoretical analyses to proof their soundness and experimental results to illustrate th eir efficiency. Title: Publishing Search Logs – A Comparative Study of Privacy Guarantees Search engine companies collect the “database of intentions”, the histories of their users’ search queries. These search logs are a gold mine for researchers. Search engine companies, however, are wary of publishing search logs in order not to disclose sensitive information. In this paper we analyze algorithms for publishing frequent keywords, queries and clicks of a search log. We first show how methods that achieve variants of k-anonymity are vulnerable to active attacks. We then demonstrate that the stronger guarantee ensured by differential privacy unfortunately does not provide any utility for this problem. Our paper concludes with a large experimental study using real applications where we compare ZEALOUS and previous work that achieves k-anonymity in search log publishing. Our results show that ZEALOUS yields comparable utility to k−anonymity while at the same time achieving much stronger priva cy guarantees. Title: Robust Correlation of Encrypted Attack Traffic through Stepping Stones by Flow Watermarking Network based intruders seldom attack their victims directly from their own computer. Often, they stage their attacks through intermediate “stepping stones” in order to conceal their identity and origin. To identify the source of the attack behind the stepping stone(s), it is necessary to correlate the incoming and outgoing flows or connections of a stepping stone. To resist attempts at correlation, the attacker may encrypt or otherwise manipulate the connection traffic. Timing based correlation approaches have been shown to be quite effective in correlating encrypted connections. However, timing based correlation approaches are subject to timing perturbations that may be deliberately
- 12. Core IEEE Projects (Division of Conceptz) #108,5th Main, 4th Cross, Hanumanth Nagar, Basavanagudi, Bangalore-50, Website: www.coreieeeprojects.com contact: 9535052050 introduced by the attacker at stepping stones. In this project, our watermark - based approach is “active” in that It embeds a unique watermark into the encrypted flows by slightly adjusting the timing of selected packets. The unique watermark that is embedded in the encrypted flow gives us a number of advantages over passive timing based correlation in resisting timing perturbations by the attacker. A two-fold monotonically increasing compound mapping i s created and proved to yield more distinctive visible watermarks in the watermarked image. Security protection measures by parameter and mapping randomizations have also been proposed to deter attackers from illicit image recoveries. Title: Scalable Learning of Collective Behavior This study of collective behavior is to understand how individuals behave in a social networking environment. Oceans of data generated by social media like Face book, Twitter, Flicker, and YouTube present opportu nities 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 individu als 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.
- 13. Core IEEE Projects (Division of Conceptz) #108,5th Main, 4th Cross, Hanumanth Nagar, Basavanagudi, Bangalore-50, Website: www.coreieeeprojects.com contact: 9535052050 Title: The Awareness Network, To Whom Should I Display My Actions And, Whose Actions Should I Monitor The concept of awareness plays a pivotal role in research in Computer -Supported Cooperative Work. Recently, Software Engineering researchers interested in the collaborative nature of software development have explored the implications of this concept in the design of software development tools. A critical aspect of awareness is the associated coordinative work practices of displaying and monitoring actions. This aspect concerns how colleagues monitor one another’s actions to understand how these actions impact their own work and how they display their actions in such a way that others can easily monitor them while doing their own work. In this paper, we focus on an additional aspect of awareness: the identification of the social actors who should be monitored and the actors to whom their actions should be displayed. We address this aspect by presenting software developers’ work practices based on ethnographic data from three different software development teams. In addition, we illustrate how these work practices are influenced by different factors, including the organizational setting, the age of the project, and the software architecture. We discuss how our results are relevant for both CSCW and Software Engineering researchers. Title: The Awareness Network, To Whom Should I Display My Actions And, Whose Actions Should I Monitor This study of collective behavior is to understand how individuals behave in a social networking environment. 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 conn ections 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 addres s 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 predictio n performance to other non-scalable methods.
- 14. Core IEEE Projects (Division of Conceptz) #108,5th Main, 4th Cross, Hanumanth Nagar, Basavanagudi, Bangalore-50, Website: www.coreieeeprojects.com contact: 9535052050 Title: Throughput Optimization in High Speed Downlink Packet Access (HSDPA) In this paper, we investigate throughput optimization in High Speed Downlink Packet Access (HSDPA). Specifically, we propose offl ine and online algorithms for adjusting the Channel Quality Indicator (CQI) used by the network to schedule data transmission. In the offline algorithm, a given target BLER is achieved by adjusting CQI based on ACK/NAK history. By sweeping through differen t target BLERs, we can find the throughput optimal BLER offline. This algorithm could be used not only to optimize throughput but also to enable fair resource allocation among mobile users in HSDPA. In the online algorithm, the CQI offset is adapted using an estimated short term throughput gradient without specifying a target BLER. An adaptive stepsize mechanism is proposed to track temporal variation of the environment. We investigate convergence behavior of both algorithms. Simulation results show that the proposed offline algorithm can achieve the given target BLER with good accuracy. Both algorithms yield up to 30% HSDPA throughput improvement over that with 10% target BLER. Title: USHER Improving Data Quality with Dynamic Forms Data quality is a critical problem in modern databases. Data entry forms present the first and arguably best opportunity for detecting and mitigating errors, but there has been little research into automatic methods for improving data quality at entry time. In this paper, we propose USHER, an end-to-end system for form design, entry, and data quality assurance. Using previous form submissions, USHER learns a probabilistic model over the questions of the form. USHER then applies this model at every step of t he data entry process to improve data quality. Before entry, it induces a form layout that captures the most important data values of a form instance as quickly as possible. During entry, it dynamically adapts the form to the values being entered, and enab les real-time feedback to guide the data enterer toward their intended values. After entry, it re -asks questions that it deems likely to have been entered incorrectly. We evaluate all three components of USHER using two real-world data sets. Our results demonstrate that each component has the potential to improve data quality considerably, at a reduced cost when compared to current practice.