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2011 ieee projects


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2011 ieee projects

  1. 1. #241/85, 4th floor, Rangarajapuram main road, Kodambakkam (Power House) Chennai 600024 ,, 08428302179 / 044-42046028S.NO TITLE -2010 ABSTRACT DOMAIN PLATFORM 1. A Machine Learning TCP throughput prediction is an important capability for Networking .net Approach to TCP networks where multiple paths exist between data Throughput senders and receivers. In this paper, we describe a new Prediction lightweight method for TCP throughput prediction. Our predictor uses Support Vector Regression (SVR); prediction is based on both prior file transfer history and measurements of simple path properties. We evaluate our predictor in a laboratory setting where ground truth can be measured with perfect accuracy. We report the performance of our predictor for oracular and practical measurements of path properties over a wide range of traffic conditions and transfer sizes. For bulk transfers in heavy traffic using oracular measurements, TCP throughput is predicted within 10% of the actual value 87% of the time, representing nearly a threefold improvement in accuracy over prior history-based methods. For practical measurements of path properties, predictions can be made within 10% of the actual value nearly 50% of the time, approximately a 60% improvement over history-based methods, and with much lower measurement traffic overhead. We implement our predictor in a tool called PathPerf, test it in the wide area, and show that PathPerf predicts TCP throughput accurately over diverse wide area paths. 2. Feedback-Based A framework for designing feedback-based scheduling .net Scheduling for Load- algorithms is proposed for elegantly solving the Balanced Two-Stage notorious packet missequencing problem of a load- Switches balanced switch. Unlike existing approaches, we show that the efforts made in load balancing and keeping packets in order can complement each other. Specifically, at each middle-stage port between the two switch fabrics of a load-balanced switch, only a single-packet buffer for each virtual output queueing (VOQ) is required. Although packets belonging to the same flow pass through different middle-stage VOQs, the delays they experience at different middle-stage ports will be identical. This is made possible by properly selecting and coordinating the two sequences of switch configurations to form a joint sequence with both staggered symmetry property and in-order packet delivery property. Based on the staggered symmetry property, an efficient feedback mechanism is designed to allow the right middle-stage port occupancy vector to be delivered to the right input port at the right time. As a result, the performance of load balancing as well as the switch throughput is significantly improved. We further extend this feedback mechanism to support the multicabinet implementation of a load-balanced switch, where the propagation delay between switch linecards and switch fabrics is nonnegligible. As compared to the existing load-balanced switch architectures and scheduling algorithms, our solutions impose a modest requirement on switch hardware, but consistently yield better delay-throughput performance. Last but not least, some extensions and refinements are made to address the scalability, implementation, and fairness issues of our solutions.
  2. 2. #241/85, 4th floor, Rangarajapuram main road, Kodambakkam (Power House) Chennai 600024 ,, 08428302179 / 044-42046028 3. Trust management in In this paper, we propose a human-based model which .net mobile ad hoc networks builds a trust relationship between nodes in an ad hoc using a scalable maturity network. The trust is based on previous individual based model experiences and on the recommendations of others. We present the Recommendation Exchange Protocol (REP) which allows nodes to exchange recommendations about their neighbors. Our proposal does not require disseminating the trust information over the entire network. Instead, nodes only need to keep and exchange trust information about nodes within the radio range. Without the need for a global trust knowledge, our proposal scales well for large networks while still reducing the number of exchanged messages and therefore the energy consumption. In addition, we mitigate the effect of colluding attacks composed of liars in the network. A key concept we introduce is the relationship maturity, which allows nodes to improve the efficiency of the proposed model for mobile scenarios. We show the correctness of our model in a single-hop network through simulations. We also extend the analysis to mobile multihop networks, showing the benefits of the maturity relationship concept. We evaluate the impact of malicious nodes that send false recommendations to degrade the efficiency of the trust model. At last, we analyze the performance of the REP protocol and show its scalability. We show that our implementation of REP can significantly reduce the number messages. 4. Online social networks OSNs applications, it is a location-based social network Network .net services, security and privacy of OSNs, and human mobility models based on social network OSNs online service site focuses of social networks or social relations among people, e.g., who share interests and activities. A social network service essentially consists of a representation of each user (often a profile), his/her social links, and a variety of additional services. Most social network services are web based and provide means for users to interact over the internet, such as e-mail and instant messaging. Although online community services are sometimes considered as a social network online community services are group- centered. Social networking sites allow users to share ideas, activities, events, and interests within their individual networks. 5. SYNCHRONIZATION OF File synchronization in computing is the process of LOCAL DESKTOP TO making sure that files in two or more locations are INTERNET USING FILE updated through certain rules. In one-way file TRANSFER PROTOCOL synchronization, also called mirroring, updated files are copied from a source location to one or more target locations, but no files are copied back to the source location. In two-way file synchronization, updated files are copied in both directions, usually with the purpose of keeping the two locations identical to each other. In this article, the term synchronization refers exclusively to two-way file synchronization.
  3. 3. #241/85, 4th floor, Rangarajapuram main road, Kodambakkam (Power House) Chennai 600024 ,, 08428302179 / 044-42046028 6. Intrusion Detection for Providing security in a distributed system requires more Grid and Cloud than user authentication with passwords or digital Computing certificates and confidentiality in data transmission. The Grid and Cloud Computing Intrusion Detection System integrates knowledge and behavior analysis to detect intrusions. 7. Adaptive Physical Transmit power and carrier sense threshold are key Carrier Sense in MAC/PHY parameters in carrier sense multiple access Topology-Controlled (CSMA) wireless networks. Transmit power control has Wireless Networks been extensively studied in the context of topology control. However, the effect of carrier sense threshold on topology control has not been properly investigated in spite of its crucial role. Our key motivation is that the performance of a topology-controlled network may become worse than that of a network without any topology control unless carrier sense threshold is properly chosen. In order to remedy this deficiency of conventional topology control, we present a framework on how to incorporate physical carrier sense into topology control. We identify that joint control of transmit power and carrier sense threshold can be efficiently divided into topology control and carrier sense adaptation. We devise a distributed carrier sense update algorithm (DCUA), by which each node drives its carrier sense threshold toward a desirable operating point in a fully distributed manner. We derive a sufficient condition for the convergence of DCUA. To demonstrate the utility of integrating physical carrier sense into topology control, we equip a localized topology control algorithm, LMST, with the capability of DCUA. Simulation studies show that LMST-DCUA significantly outperforms LMST and the standard 8. On the Quality of Service of We model the probabilistic behavior of a system Dependable .net Crash-Recovery Failure comprising a failure detector and a monitored crash- and Security Detectors recovery target. We extend failure detectors to take account of failure recovery in the target system. This involves extending QoS measures to include the recovery detection speed and proportion of failures detected. We also extend estimating the parameters of the failure detector to achieve a required QoS to configuring the crash-recovery failure detector. We investigate the impact of the dependability of the monitored process on the QoS of our failure detector. Our analysis indicates that variation in the MTTF and MTTR of the monitored process can have a significant impact on the QoS of our failure detector. Our analysis is supported by simulations that validate our theoretical results.
  4. 4. #241/85, 4th floor, Rangarajapuram main road, Kodambakkam (Power House) Chennai 600024 ,, 08428302179 / 044-42046028 9. Layered Approach using Intrusion detection faces challenges an intrusion conditional random field detection system must constantly detect malicious activities in a network and must perform efficiently to cope with the large amount of network traffic. These two issues of Accuracy and Efficiency using Conditional Random Fields and Layered Approach. We show that high attack detection accuracy can be achieved by using Conditional Random Fields and high efficiency by implementing the Layered Approach. Experimental results on the benchmark KDD ’99 intrusion data set show that our proposed system based on Layered Conditional Random Fields outperforms other well-known methods such as the decision trees and the naive Bayes. The improvement in attack detection accuracy is very high, particularly, for the U2R attacks (34.8 percent improvement) and the R2L attacks (34.5 percent improvement). Statistical Tests also demonstrate higher confidence in detection accuracy for our method. Finally, we show that our system is robust and is able to handle noisy data without compromising performance. 10. Privacy-Preserving Sharing Privacy-preserving sharing of sensitive information Security and .net of Sensitive Information (PPSSI) is motivated by the increasing need for entities privacy (organizations or individuals) that dont fully trust each other to share sensitive information. Many types of entities need to collect, analyze, and disseminate data rapidly and accurately, without exposing sensitive information to unauthorized or untrusted parties. Although statistical methods have been used to protect data for decades, they arent foolproof and generally involve a trusted third party. Recently, the security research community has studied—and, in a few cases, deployed—techniques using secure, multiparty function evaluation, encrypted keywords, and private information retrieval. However, few practical tools and technologies provide data privacy, especially when entities have certain common goals and require (or are mandated) some sharing of sensitive information. To this end, PPSSI technology aims to enable sharing information, without exposing more than the minimum necessary to complete a common task. 11. PEACE Security and privacy issues are of most concern in pushing the success of WMNs(Wireless Mesh Networks) for their wide deployment and for supporting service-oriented applications. Despite the necessity, limited security research has been conducted toward privacy preservation in WMNs. This motivates us to develop PEACE, a novel Privacy- Enhanced yet Accountable security framework, tailored for WMNs
  5. 5. #241/85, 4th floor, Rangarajapuram main road, Kodambakkam (Power House) Chennai 600024 ,, 08428302179 / 044-42046028 12. The Phish-Market Protocol: One way banks mitigate phishings effects is to remove .net Secure Sharing Between fraudulent websites or suspend abusive domain Competitors names. The removal process, called a "take-down," is often subcontracted to specialist firms, who refuse to share feeds of phishing website URLs with each other. Consequently, many phishing websites arent removed. The take-down companies are reticent to exchange feeds, fearing that competitors with less comprehensive lists might free-ride off their efforts. Here, the authors propose the Phish-Market protocol, which enables companies to be compensated for information they provide to their competitors, encouraging them to share. The protocol is designed so that the contributing firm is compensated only for those websites affecting its competitors clients and only those previously unknown to the receiving firm. The receiving firm, on the other hand, is guaranteed privacy for its client list. The protocol solves a more general problem of sharing between competitors; applications to data brokers in marketing, finance, energy exploration, and beyond could also benefit. 13. Internet Filtering Issues Various governments have been considering .net and Challenges mechanisms to filter out illegal or offensive Internet material. The accompanying debate raises a number of questions from a technical perspective. This article explores some of these questions, such as, what filtering techniques exist,are they effective in filtering out the specific content, how easy is circumventing them ,where should they be placed in the Internet architecture. 14. Can Public-Cloud Security Because cloud-computing environments security .net Meet Its Unique vulnerabilities differ from those of traditional data Challenges? centers, perimeter-security approaches will no longer work. Security must move from the perimeter to the virtual machines. 15. Encrypting Keys Securely Encryption keys are sometimes encrypted themselves; .net doing that properly requires special care. Although it might look like an oversight at first, the broadly accepted formal security definitions for cryptosystems dont allow encryption of key-dependent messages. Furthermore, key-management systems frequently use key encryption or wrapping, which might create dependencies among keys that lead to problems with simple access-control checks. Security professionals should be aware of this risk and take appropriate measures. Novel cryptosystems offer protection for key-dependent messages and should be considered for practical use. Through enhanced access control in key- management systems, you can prevent security- interface attacks. 16. Auto-Context and Its The notion of using context information for solving Pattern .net Application to High-Level high-level vision and medical image segmentation Analysis and Vision Tasks and 3D Brain problems has been increasingly realized in the field. Machine Image Segmentation However, how to learn an effective and efficient Intelligence context model, together with an image appearance
  6. 6. #241/85, 4th floor, Rangarajapuram main road, Kodambakkam (Power House) Chennai 600024 ,, 08428302179 / 044-42046028 model, remains mostly unknown. The current literature using Markov Random Fields (MRFs) and Conditional Random Fields (CRFs) often involves specific algorithm design in which the modeling and computing stages are studied in isolation. In this paper, we propose a learning algorithm, auto-context. Given a set of training images and their corresponding label maps, we first learn a classifier on local image patches. The discriminative probability (or classification confidence) maps created by the learned classifier are then used as context information, in addition to the original image patches, to train a new classifier. The algorithm then iterates until convergence. Auto-context integrates low-level and context information by fusing a large number of low- level appearance features with context and implicit shape information. The resulting discriminative algorithm is general and easy to implement. Under nearly the same parameter settings in training, we apply the algorithm to three challenging vision applications: foreground/background segregation, human body configuration estimation, and scene region labeling. Moreover, context also plays a very important role in medical/brain images where the anatomical structures are mostly constrained to relatively fixed positions. With only some slight changes resulting from using 3D instead of 2D features, the auto-context algorithm applied to brain MRI image segmentation is shown to outperform state-of-the-art algorithms specifically designed for this domain. Furthermore, the scope of the proposed algorithm goes beyond image analysis and it has the potential to be used for a wide variety of problems for structured prediction problems. 17. CSMA protocol Mitigating This system is developed to show the descriptive java Performance Degradation management of dreadful conditions in Congested in Congested Sensor Sensor Networks. The dreadful conditions in sensor Networks networks or any other wired networks will happen when bandwidth differs from receiving and sending points. The channel capacity of the network may not be sufficient enough to handle the speed of packets sent. In this system, we are presenting a view, how the data can be sent through the congested channel and also the safe delivery of the packets to the destination. This System is developed using java swing technology with jdk1.6. All the nodes are developed as swing API‘s.Multiple API‘s form a sink to the destination. The packets will be sent from Source to destination, via sink. In the sink, a node will be made congested and using channel capacity, the path of data will be calculated. Based on the result of the calculation, the congestion in the sink will be dissolved and data is set free to the destination.This system is an application to maintain the free flow of data in congested sensor networks using Differentiated Routing Protocol and Priority Queues, which maintain priority in data-types.
  7. 7. #241/85, 4th floor, Rangarajapuram main road, Kodambakkam (Power House) Chennai 600024 ,, 08428302179 / 044-42046028 18. Feature Analysis and The definition of parameters is a crucial step in the Multimedia .net Evaluation for Automatic development of a system for identifying emotions in Emotion Identification in speech. Although there is no agreement on which are Speech the best features for this task, it is generally accepted that prosody carries most of the emotional information. Most works in the field use some kind of prosodic features, often in combination with spectral and voice quality parametrizations. Nevertheless, no systematic study has been done comparing these features. This paper presents the analysis of the characteristics of features derived from prosody, spectral envelope, and voice quality as well as their capability to discriminate emotions. In addition, early fusion and late fusion techniques for combining different information sources are evaluated. The results of this analysis are validated with experimental automatic emotion identification tests. Results suggest that spectral envelope features outperform the prosodic ones. Even when different parametrizations are combined, the late fusion of long-term spectral statistics with short-term spectral envelope parameters provides an accuracy comparable to that obtained when all parametrizations are combined. 19. Automatic Detection of Off- Identifying off-task behaviors in intelligent tutoring Learning .net Task Behaviors in systems is a practical and challenging research topic. Technologie Intelligent Tutoring This paper proposes a machine learning model that s Systems with Machine can automatically detect students off-task behaviors. Learning Techniques The proposed model only utilizes the data available from the log files that record students actions within the system. The model utilizes a set of time features, performance features, and mouse movement features, and is compared to 1) a model that only utilizes time features and 2) a model that uses time and performance features. Different students have different types of behaviors; therefore, personalized version of the proposed model is constructed and compared to the corresponding nonpersonalized version. In order to address data sparseness problem, a robust Ridge Regression algorithm is utilized to estimate model parameters. An extensive set of experiment results demonstrates the power of using multiple types of evidence, the personalized model, and the robust Ridge Regression algorithm. 20. Web-Application Security: Heres a sobering thought for all managers responsible IT .net From Reactive to Proactive for Web applications: Without proactive consideration for an applications security, attackers can bypass nearly all lower-layer security controls simply by using the application in a way its developers didnt envision. Learn how to address vulnerabilities proactively and early on to avoid the devastating consequences of a successful attack. 21. Trust and Reputation Trust and reputation management research is highly INTERNET .net Management interdisciplinary, involving researchers from COMPUTING networking and communication, data management and information systems, e-commerce and service computing, artificial intelligence, and game theory, as
  8. 8. #241/85, 4th floor, Rangarajapuram main road, Kodambakkam (Power House) Chennai 600024 ,, 08428302179 / 044-42046028 well as the social sciences and evolutionary biology. Trust and reputation management has played and will continue to play an important role in Internet and social computing systems and applications. This special issue addresses key issues in the field, such as representation, recommendation aggregation, and attack-resilient reputation systems. 22. Multi-body Structure-and- An efficient and robust framework is proposed for Image .net Motion Segmentation by two-view multiple structure-and-motion segmentation Processing Branch-and-Bound Model of unknown number of rigid objects. The segmentation Selection problem has three unknowns, namely the object memberships, the corresponding fundamental matrices, and the number of objects. To handle this otherwise recursive problem, hypotheses for fundamental matrices are generated through local sampling. Once the hypotheses are available, a combinatorial selection problem is formulated to optimize a model selection cost which takes into account the hypotheses likelihoods and the model complexity. An explicit model for outliers is also added for robust segmentation. The model selection cost is minimized through the branch-and-bound technique of combinatorial optimization. The proposed branch- and-bound approach efficiently searches the solution space and guaranties optimality over the current set of hypotheses. The efficiency and the guarantee of optimality of the method is due to its ability to reject solutions without explicitly evaluating them. The proposed approach was validated with synthetic data, and segmentation results are presented for real images. 23. Active Image Re ranking Image search reranking methods usually fail to .net capture the users intention when the query term is ambiguous. Therefore, reranking with user interactions, or active reranking, is highly demanded to effectively improve the search performance. The essential problem in active reranking is how to target the users intention. To complete this goal, this paper presents a structural information based sample selection strategy to reduce the users labeling efforts. Furthermore, to localize the users intention in the visual feature space, a novel local-global discriminative dimension reduction algorithm is proposed. In this algorithm, a submanifold is learned by transferring the local geometry and the discriminative information from the labelled images to the whole (global) image database. Experiments on both synthetic datasets and a real Web image search dataset demonstrate the effectiveness of the proposed active reranking scheme, including both the structural information based active sample selection strategy and the local-global discriminative dimension reduction algorithm. 24. Content Based Image An innovative approach based on an evolutionary .net Retrieval using PSO stochastic algorithm, namely the Particle Swarm Optimizer (PSO), is proposed in this paper as a
  9. 9. #241/85, 4th floor, Rangarajapuram main road, Kodambakkam (Power House) Chennai 600024 ,, 08428302179 / 044-42046028 solution to the problem of intelligent retrieval of images in large databases. The problem is recast to an optimization one, where a suitable cost function is minimized through a customized PSO. Accordingly, the relevance-feedback is used in order to exploit the information of the user with the aim of both guiding the particles inside the search space and dynamically assigning different weights to the features. 25. Automatic Composition of This paper presents a novel approach for semantic .net Semantic Web Services An web service composition based on traditional state Enhanced State Space space search approach. We regard automatic web Search Approach service composition problem as an AI problem-solving problem and propose an enhanced state space search approach toward web service composition domain. This approach can not only be used for automatic service composition, but also for general problem- solving domain. In addition, in order to validate the feasibility of our approach, a prototype system is implemented. 26. Knowledge-first web Although semantic technologies arent used in current .net services an E-Government software systems on a large scale yet, they offer high example potential to significantly improve the quality of electronic services especially in the E-Government domain. This paper therefore presents an approach that not only incorporates semantic technologies but allows to create E-Government services solely based on semantic models. This multiplies the benefits of the ontology modeling efforts, minimizes development and maintenance time and costs, improves user experience and enforces transparency. 27. The Applied Research of This paper firstly introduces the characteristics of the Cloud .net Cloud Computing Platform current E-Learning, and then analyzes the concept and Architecture In the E- characteristics of cloud computing, and describes the computing Learning Area architecture of cloud computing platform; by combining the characteristics of E-Learning and learning from current major infrastructure approach of cloud computing platform, this paper structures a relatively complete set of integration and use in one of the E-Learning platform, puts the cloud computing platform apply to the study of E-Learning, and focus on the application in order to improve the resources stability, balance and utilization; under the conditions, this platform will meet the demand for the current teaching and research activities, improve the greatest value of the E-Learning. 28. Cloud Computing System Cloud computing provides people a way to share large .net Based on Trusted mount of distributed resources belonging to different Computing Platform organizations. That is a good way to share many kinds of distributed resources, but it also makes security problems more complicate and more important for users than before. In this paper, we analyze some security requirements in cloud computing environment. Since the security problems both in software and hardware, we provided a method to build a trusted computing environment for cloud
  10. 10. #241/85, 4th floor, Rangarajapuram main road, Kodambakkam (Power House) Chennai 600024 ,, 08428302179 / 044-42046028 computing by integrating the trusted computing platform (TCP) into cloud computing system. We propose a new prototype system, in which cloud computing system is combined with Trusted Platform Support Service (TSS) and TSS is based on Trusted Platform Module (TPM). In this design, better effect can be obtained in authentication, role based access and data protection in cloud computing environment. 29. IT Auditing to Assure a In this paper we discuss the evolvement of cloud .net Secure Cloud Computing. computing paradigm and present a framework for secure cloud computing through IT auditing. Our approach is to establish a general framework using checklists by following data flow and its lifecycle. The checklists are made based on the cloud deployment models and cloud services models. The contribution of the paper is to understand the implication of cloud computing and what is meant secure cloud computing via IT auditing rather than propose a new methodology and new technology to secure cloud computing. Our holistic approach has strategic value to those who are using or consider using cloud computing because it addresses concerns such as security, privacy and regulations and compliance. 30. Performance Evaluation of Advanced computing on cloud computing .net Cloud Computing Offerings infrastructures can only become viable alternative for the enterprise if these infrastructures can provide proper levels of nonfunctional properties (NPFs). A company that focuses on service-oriented architectures (SOA) needs to know what configuration would provide the proper levels for individual services if they are deployed in the cloud. In this paper we present an approach for performance evaluation of cloud computing configurations. While cloud computing providers assure certain service levels, this it typically done for the platform and not for a particular service instance. Our approach focuses on NFPs of individual services and thereby provides a more relevant and granular information. An experimental evaluation in Amazon Elastic Compute Cloud (EC2) verified our approach. 31. Providing Privacy People can only enjoy the full benefits of Cloud .net Preserving in cloud computing if we can address the very real privacy and computing security concerns that come along with storing sensitive personal information in databases and software scattered around the Internet. There are many service provider in the internet, we can call each service as a cloud, each cloud service will exchange data with other cloud, so when the data is exchanged between the clouds, there exist the problem of disclosure of privacy. So the privacy disclosure problem about individual or company is inevitably exposed when releasing or sharing data in the cloud service. Privacy is an important issue for cloud computing, both in terms of legal compliance and user
  11. 11. #241/85, 4th floor, Rangarajapuram main road, Kodambakkam (Power House) Chennai 600024 ,, 08428302179 / 044-42046028 trust, and needs to be considered at every phase of design. Our paper provides some privacy preserving technologies used in cloud computing services. 32. VEBEK: Virtual Energy- Designing cost-efficient, secure network protocols for Wireless .net Based Encryption and Wireless Sensor Networks (WSNs) is a challenging Computing Keying for Wireless Sensor problem because sensors are resource-limited Networks wireless devices. Since the communication cost is the most dominant factor in a sensors energy consumption, we introduce an energy-efficient Virtual Energy-Based Encryption and Keying (VEBEK) scheme for WSNs that significantly reduces the number of transmissions needed for rekeying to avoid stale keys. In addition to the goal of saving energy, minimal transmission is imperative for some military applications of WSNs where an adversary could be monitoring the wireless spectrum. VEBEK is a secure communication framework where sensed data is encoded using a scheme based on a permutation code generated via the RC4 encryption mechanism. The key to the RC4 encryption mechanism dynamically changes as a function of the residual virtual energy of the sensor. Thus, a one-time dynamic key is employed for one packet only and different keys are used for the successive packets of the stream. The intermediate nodes along the path to the sink are able to verify the authenticity and integrity of the incoming packets using a predicted value of the key generated by the senders virtual energy, thus requiring no need for specific rekeying messages. VEBEK is able to efficiently detect and filter false data injected into the network by malicious outsiders. The VEBEK framework consists of two operational modes (VEBEK-I and VEBEK-II), each of which is optimal for different scenarios. In VEBEK-I, each node monitors its one-hop neighbors where VEBEK-II statistically monitors downstream nodes. We have evaluated VEBEKs feasibility and performance analytically and through simulations. Our results show that VEBEK, without incurring transmission overhead (increasing packet size or sending control messages for rekeying), is able to eliminate malicious data from the network in an energy-efficient manner. We also show that our framework performs be- - tter than other comparable schemes in the literature with an overall 60-100 percent improvement in energy savings without the assumption of a reliable medium access control layer. 33. Secure Data Collection in Compromised node and denial of service are two key .net Wireless Sensor Networks attacks in wireless sensor networks (WSNs). In this Using Randomized paper, we study data delivery mechanisms that can Dispersive Routes with high probability circumvent black holes formed by these attacks. We argue that classic multipath routing approaches are vulnerable to such attacks, mainly due to their deterministic nature. So once the adversary acquires the routing algorithm, it can compute the same routes known to the source, hence, making all information sent over these routes vulnerable to its attacks. In this paper, we develop
  12. 12. #241/85, 4th floor, Rangarajapuram main road, Kodambakkam (Power House) Chennai 600024 ,, 08428302179 / 044-42046028 mechanisms that generate randomized multipath routes. Under our designs, the routes taken by the ?? shares?? of different packets change over time. So even if the routing algorithm becomes known to the adversary, the adversary still cannot pinpoint the routes traversed by each packet. Besides randomness, the generated routes are also highly dispersive and energy efficient, making them quite capable of circumventing black holes. We analytically investigate the security and energy performance of the proposed schemes. We also formulate an optimization problem to minimize the end-to-end energy consumption under given security constraints. Extensive simulations are conducted to verify the validity of our mechanisms. 34. Aging Bloom Filter with A Bloom filter is a simple but powerful data structure Data Mining .net Two Active Buffers for that can check membership to a static set. As Bloom Dynamic Sets. filters become more popular for network applications, a membership query for a dynamic set is also required. Some network applications require high-speed processing of packets. For this purpose, Bloom filters should reside in a fast and small memory, SRAM. In this case, due to the limited memory size, stale data in the Bloom filter should be deleted to make space for new data. Namely the Bloom filter needs aging like LRU caching. In this paper, we propose a new aging scheme for Bloom filters. The proposed scheme utilizes the memory space more efficiently than double buffering, the current state of the art. We prove theoretically that the proposed scheme outperforms double buffering. We also perform experiments on real Internet traces to verify the effectiveness of the proposed scheme. 35. Bayesian Classifiers The Bayesian classifier is a fundamental classification .net Programmed in SQL technique. In this work, we focus on programming Bayesian classifiers in SQL. We introduce two classifiers: naive Bayes and a classifier based on class decomposition using K-means clustering. We consider two complementary tasks: model computation and scoring a data set. We study several layouts for tables and several indexing alternatives. We analyze how to transform equations into efficient SQL queries and introduce several query optimizations. We conduct experiments with real and synthetic data sets to evaluate classification accuracy, query optimizations, and scalability. Our Bayesian classifier is more accurate than naive Bayes and decision trees. Distance computation is significantly accelerated with horizontal layout for tables, denormalization, and pivoting. We also compare naive Bayes implementations in SQL and C++: SQL is about four times slower. Our Bayesian classifier in SQL achieves high classification accuracy, can efficiently analyze large data sets, and has linear scalability.
  13. 13. #241/85, 4th floor, Rangarajapuram main road, Kodambakkam (Power House) Chennai 600024 ,, 08428302179 / 044-42046028 36. Using a web-based tool to Top-down process improvement approaches provide a java define and implement high-level model of what the process of a software software process development organisation should be. Such models are improvement initiatives in based on the consensus of a designated working group a small industrial setting on how software should be developed or maintained. They are very useful in that they provide general guidelines on where to start improving, and in which order, to people who do not know how to do it. However, the majority of models have only worked in scenarios within large companies. The authors aim to help small software development organisations adopt an iterative approach by providing a process improvement web-based tool. This study presents research into a proposal which states that a small organisation may use this tool to assess and improve their software process, identifying and implementing a set of agile project management practices that can be strengthened using the CMMI-DEV 1.2 model as reference. 37. An Online Monitoring 2 Web service technology aims to enable the Java Approach for Web Service interoperation of heterogeneous systems and the Requirements reuse of distributed functions in an unprecedented (An Online Monitoring scale and has achieved significant success. There are Approach for Web Service still, however, challenges to realize its full potential. Requirements –web One of these challenges is to ensure the behaviour of services(ME)) Web services consistent with their requirements. Monitoring events that are relevant to Web service requirements is, thus, an important technique. This paper introduces an online monitoring approach for Web service requirements. It includes a pattern-based specification of service constraints that correspond to service requirements, and a monitoring model that covers five kinds of system events relevant to client request, service response, application, resource, and management, and a monitoring framework in which different probes and agents collect events and data that are sensitive to requirements. The framework analyzes the collected information against the prespecified constraints, so as to evaluate the behaviour and use of Web services. The prototype implementation and experiments with a case study shows that our approach is effective and flexible, and the monitoring cost is affordable.
  14. 14. #241/85, 4th floor, Rangarajapuram main road, Kodambakkam (Power House) Chennai 600024 ,, 08428302179 / 044-42046028S.NO TITLE -2011 ABSTRACT DOMAIN PLATFORM 1. Exploiting Dynamic In recent years ad hoc parallel data processing has Parallel Resource Allocation emerged to be one of the killer applications for Distribution for Efficient Parallel Infrastructure-as-a-Service (IaaS) clouds. Major Cloud Data Processing in computing companies have started to integrate the Cloud 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 Nephele. Nephele is the first data processing framework to explicitly exploit the dynamic resource allocation offered by todays 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. Based on this new framework, we perform extended evaluations of MapReduce-inspired processing jobs on an IaaS cloud system and compare the results to the popular data processing framework Hadoop. 2. Data integrity proofs Cloud computing has been envisioned as the de-facto Communicat in cloud storage solution to the rising storage costs of IT Enterprises. ion System & With the high costs of data storage devices as well as the network 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. One of the important concerns that need to be addressed is to assure the customer of the integrity i.e. correctness of his data in the cloud. As the data is physically not accessible to the user the cloud should provide a way for the user to check if the integrity of his data is maintained or is compromised. In this paper we provide a scheme 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). This scheme ensures that the storage at the client side is minimal which will be beneficial for thin clients. 3. Efficient Computing In many applications, including location based services, Knowledge of Range Aggregates queries are not precise. In this paper, we study the & data against Uncertain problem of efficiently computing range aggregates in a engineering Location Based multi-dimensional space when the query location is uncertain. That is, for a set of data points P, an uncertain
  15. 15. #241/85, 4th floor, Rangarajapuram main road, Kodambakkam (Power House) Chennai 600024 ,, 08428302179 / 044-42046028 Collections location based query Q with location described by a probabilistic density function, we want to calculate the aggregate information (e.g., count, average} and sum) of the data points within distance gamma to Q with probability at least theta. We propose novel, efficient techniques to solve the problem based on a filtering-and- verification framework. In particular, two novel filtering techniques are proposed to effectively and efficiently remove data points from verification. Finally, we show that our techniques can be immediately extended to solve the range query problem. Comprehensive experiments conducted on both real and synthetic data demonstrate the efficiency and scalability of our techniques. 4. Exploring Natural phenomena show that many creatures form Knowledge Application-Level large social groups and move in regular patterns. & Data Semantics for Data However, previous works focus on finding the movement Engineering Compression 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 maximum 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. 5. Improving Aggregate Recommender systems are becoming increasingly Knowledge Recommendation important to individual users and businesses for & Data Diversity Using providing personalized recommendations. However, Engineering Ranking-Based while the majority of algorithms proposed in Techniques recommender systems literature have focused on improving recommendation accuracy (as exemplified by the recent Netflix Prize competition), other important aspects of recommendation quality, such as the diversity of recommendations, have often been overlooked. In this paper, we introduce and explore a number of item ranking techniques that can generate recommendations that have substantially higher aggregate diversity across all users while maintaining comparable levels of recommendation accuracy. Comprehensive empirical evaluation consistently shows the diversity gains of the proposed techniques using several real-world rating datasets and different rating prediction algorithms. 6. Monitoring Service Business processes are increasingly distributed and Service Systems from a open, making them prone to failure. Monitoring is, Computing Language-Action therefore, an important concern not only for the processes themselves but also for the services that
  16. 16. #241/85, 4th floor, Rangarajapuram main road, Kodambakkam (Power House) Chennai 600024 ,, 08428302179 / 044-42046028 Perspective 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 varied abstraction levels. We demonstrate how the framework can be implemented and evaluate it with multiple scenarios that include specifying and monitoring open- service policy commitments. 7. One Size Does Not Fit With the emergence of the deep Web databases, Knowledge All Towards User- searching in domains such as vehicles, real estate, etc. & data and Query- has become a routine task. One of the problems in this engineering Dependent Ranking context is ranking the results of a user query. Earlier For Web Databases 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 the results of Web database queries. 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 function is acquired from a sparse workload comprising of several such ranking functions derived for various user-query pairs. The proposed 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 both analytically and experimentally over two distinct Web databases. 8. Optimal Service Cloud applications that offer data management services Knowledge Pricing for a Cloud are emerging. Such clouds support caching of data in & data Cache order to provide quality query services. The users can engineering query the cloud data, paying the price for the infrastructure they use. Cloud management necessitates an economy that manages the service of 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 study shows the efficiency of the solution. 9. A Personalized As a model for knowledge description and formalization, Knowledge Ontology Model for ontologies are widely used to represent user profiles in & data Web Information personalized web information gathering. However, when engineering Gathering representing user profiles, many models have utilized only knowledge from either a global knowledge base or a
  17. 17. #241/85, 4th floor, Rangarajapuram main road, Kodambakkam (Power House) Chennai 600024 ,, 08428302179 / 044-42046028 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. 10. A Branch-and-Bound In branch-and-bound (B&B) schemes for solving a Computers Algorithm for Solving minimization problem, a better lower bound could prune the Multiprocessor many meaningless branches which do not lead to an Scheduling Problem optimum solution. In this paper, we propose several with Improved techniques to refine the lower bound on the makespan in Lower Bounding the multiprocessor scheduling problem (MSP). The key Techniques idea of our proposed method is to combine an efficient quadratic-time algorithm for calculating the Fernándezs bound, which is known as the best lower bounding technique proposed in the literature with two improvements based on the notions of binary search and recursion. The proposed method was implemented as a part of a B&B algorithm for solving MSP, and was evaluated experimentally. The result of experiments indicates that the proposed method certainly improves the performance of the underlying B&B scheme. In particular, we found that it improves solutions generated by conventional heuristic schemes for more than 20 percent of randomly generated instances, and for more than 80 percent of instances, it could provide a certification of optimality of the resulting solutions, even when the execution time of the B&B scheme is limited by one minute. 11. Design and Peer-to-peer (P2P) systems generate a major fraction of Computers Evaluation of a Proxy the current Internet traffic, and they significantly Cache for Peer-to- increase the load on ISP networks and the cost of Peer Traffic running and connecting customer networks (e.g., universities and companies) to the Internet. To mitigate these negative impacts, many previous works in the literature have proposed caching of P2P traffic, but very few (if any) have considered designing a caching system to actually do it. This paper demonstrates that caching P2P traffic is more complex than caching other Internet traffic, and it needs several new algorithms and storage systems. Then, the paper presents the design and evaluation of a complete, running, proxy cache for P2P traffic, called pCache. pCache transparently intercepts and serves traffic from different P2P systems. A new storage system is proposed and implemented in pCache. This storage system is optimized for storing P2P traffic, and it is shown to outperform other storage systems. In addition, a new algorithm to infer the information required to store and serve P2P traffic by the cache is proposed. Furthermore, extensive experiments to evaluate all aspects of pCache using actual implementation and real P2P traffic are presented. 12. Robust Feature Feature selection often aims to select a compact feature Computation Selection for subset to build a pattern classifier with reduced al Biology Microarray Data complexity, so as to achieve improved classification and Based on performance. From the perspective of pattern analysis, Bioinformati producing stable or robust solution is also a desired cs
  18. 18. #241/85, 4th floor, Rangarajapuram main road, Kodambakkam (Power House) Chennai 600024 ,, 08428302179 / 044-42046028 Multicriterion Fusion property of a feature selection algorithm. However, the issue of robustness is often overlooked in feature selection. In this study, we analyze the robustness issue existing in feature selection for high-dimensional and small-sized gene-expression data, and propose to improve robustness of feature selection algorithm by using multiple feature selection evaluation criteria. Based on this idea, a multicriterion fusion-based recursive feature elimination (MCF-RFE) algorithm is developed with the goal of improving both classification performance and stability of feature selection results. Experimental studies on five gene-expression data sets show that the MCF-RFE algorithm outperforms the commonly used benchmark feature selection algorithm SVM-RFE. 13. Image-Based Surface Emerging technologies for structure matching based on Computation Matching Algorithm surface descriptions have demonstrated their al Biology Oriented to effectiveness in many research fields. In particular, they and Structural Biology can be successfully applied to in silico studies of Bioinformati structural biology. Protein activities, in fact, are related cs to the external characteristics of these macromolecules and the ability to match surfaces can be important to infer information about their possible functions and interactions. In this work, we present a surface-matching algorithm, based on encoding the outer morphology of proteins in images of local description, which allows us to establish point-to-point correlations among macromolecular surfaces using image-processing functions. Discarding methods relying on biological analysis of atomic structures and expensive computational approaches based on energetic studies, this algorithm can successfully be used for macromolecular recognition by employing local surface features. Results demonstrate that the proposed algorithm can be employed both to identify surface similarities in context of macromolecular functional analysis and to screen possible protein interactions to predict pairing capability 14. Iris matching using Iris recognition is one of the most widely used biometric Computer multi-dimensional technique for personal identification. This identification Vision, IET artificial neural is achieved in this work by using the concept that, the iris network patterns are statistically unique and suitable for biometric measurements. In this study, a novel method of recognition of these patterns of an iris is considered by using a multidimensional artificial neural network. The proposed technique has the distinct advantage of using the entire resized iris as an input at once. It is capable of excellent pattern recognition properties as the iris texture is unique for every person used for recognition. The system is trained and tested using two publicly available databases (CASIA and UBIRIS). The proposed approach shows significant promise and potential for improvements, compared with the other conventional matching techniques with regard to time and efficiency of results. 15. Real-time tracking Many vision problems require fast and accurate tracking Computer using A* heuristic of objects in dynamic scenes. In this study, we propose Vision, IET search and template an A* search algorithm through the space of transformations for computing fast target 2D motion.