Cooperative Data Dissemination via Roadside WLANs.

ABSTRACT:-

Data dissemination services embrace a wide variety of telematic applications where data packets are generated at a remote server in the Internet and destined to a group of nomadic users such as vehicle passengers and pedestrians. The quality of a data dissemination service is highly dependent on the availability of network infrastructures in terms of the access points. In this article, we investigate the utilization of roadside wireless local area networks (RS-WLANs) as a network infrastructure for data dissemination. A two-level cooperative data dissemination approach is presented. With the network-level cooperation, the resources in the RS-WLANs are used to facilitate the data dissemination services for the nomadic users. The packet-level cooperation is exploited to improve the packet transmission rate to a nomadic user. Various techniques for the two levels of cooperation are discussed. A case study is presented to evaluate the performance of the data dissemination approach.

Keywords:- IEEE Project Titles 2012, Wireless Communication Titles, Cloud, Computing Titles, Networking Titles.

Topology Control in Mobile Ad Hoc Networks with Cooperative Communications.

ABSTRACT

Cooperative communication has received tremendous interest for wireless networks. Most existing works on cooperative communications are focused on link-level physical layer issues. Consequently, the impacts of cooperative communications on network-level upper layer issues, such as topology control, routing and network capacity, are largely ignored. In this article, we propose a Capacity-Optimized Cooperative (COCO) topology control scheme to improve the network capacity in MANETs by jointly considering both upper layer network capacity and physical layer cooperative communications. Through simulations, we show that physical layer cooperative communications have significant impacts on the network capacity, and the proposed topology control scheme can substantially improve the network capacity in MANETs with cooperative communications.

keywords: IEEE Project Titles 2012, Wireless Communication, Data Mining Titles, Cloud Computing Titles.

Bridging Social and Data Networks

ABSTRACT

Social networking applications have emerged as the platform of choice for carrying out a number of different activities online. In addition to their primary target of social interaction, we now also employ such applications to search for information online or to share multimedia content with our friends and families. For instance, according to recent statistics, each of us spends on average 15 min on YouTube every day.

 Keywords: IEEE Project Titles 2012, Data Mining Titles, Wireless Communication Titles , Networking Titles,Cloud communication Titles.  

Discovering Characterizations of the Behavior of Anomalous Sub-populations.

 ABSTRACT:-

We consider the problem of discovering attributes, or properties, accounting for the a-priori stated abnormality of a group of anomalous individuals (the outliers) with respect to an overall given population (the inliers). To this aim, we introduce the notion of exceptional property and define the concept of exceptionality score, which measures the significance of a property. In particular, in order to single out exceptional properties, we resort to a form of minimum distance estimation for evaluating the badness of fit of the values assumed by the outliers compared to the probability distribution associated with the values assumed by the inliers. Suitable exceptionality scores are introduced for both numeric and categorical attributes. These scores are, both from the analytical and the empirical point of view, designed to be effective for small samples, as it is the case for outliers. We present an algorithm, called EXPREX, for efficiently discovering exceptional properties. The algorithm is able to reduce the needed computational effort by exploring only relevant numerical intervals and by exploiting suitable pruning rules. The experimental results confirm that our technique is able to provide knowledge characterizing outliers in a natural manner.

Keywords:-  IEEE Project Titles 2012, Data Mining Titles, Cloud Computing Titles, Networking Titles.

Outsourced Similarity Search on Metric Data Assets

ABSTRACT:-

This paper considers a cloud computing setting in which similarity querying of metric data is outsourced to a service provider. The data is to be revealed only to trusted users, not to the service provider or anyone else. Users query the server for the most similar data objects to a query example. Outsourcing offers the data owner scalability and a low-initial investment. The need for privacy may be due to the data being sensitive (e.g., in medicine), valuable (e.g., in astronomy), or otherwise confidential. Given this setting, the paper presents techniques that transform the data prior to supplying it to the service provider for similarity queries on the transformed data. Our techniques provide interesting trade-offs between query cost and accuracy. They are then further extended to offer an intuitive privacy guarantee. Empirical studies with real data demonstrate that the techniques are capable of offering privacy while enabling efficient and accurate processing of similarity queries.

Keywords:- IEEE Project 2012, Data Mining Titles, Cloud Computing Titles, Networking Titles, 

SCALABLE LEARNING OF COLLECTIVE BEHAVIOR

ABSTRACT:-

This study of collective behavior is to understand how individuals behave in a social networking environment. Oceans of data generated by social media like Facebook, Twitter, Flickr, and YouTube present opportunities and challenges to study collective behavior on a large scale. In this work, we aim to learn to predict collective behavior in social media. In particular, given information about some individuals, how can we infer the behavior of unobserved individuals in the same network? A social-dimension-based approach has been shown effective in addressing the heterogeneity of connections presented in social media. However, the networks in social media are normally of colossal size, involving hundreds of thousands of actors. The scale of these networks entails scalable learning of models for collective behavior prediction. To address the scalability issue, we propose an edge-centric clustering scheme to extract sparse social dimensions. With sparse social dimensions, the proposed approach can efficiently handle networks of millions of actors while demonstrating a comparable prediction performance to other nonscalable methods.

Keywords:- IEEE Project 2012, Data Mining Titles, Wireless Communication Titles, Networking Tiles.

QUERY PLANNING FOR CONTINUOUS AGGREGATION QUERIES OVER A NETWORK OF DATA AGGREGATORS

ABSTRACT:-

Continuous queries are used to monitor changes to time varying data and to provide results useful for online decision making. Typically a user desires to obtain the value of some aggregation function over distributed data items, for example, to know value of portfolio for a client; or the AVG of temperatures sensed by a set of sensors. In these queries a client specifies a coherency requirement as part of the query. We present a low-cost, scalable technique to answer continuous aggregation queries using a network of aggregators of dynamic data items. In such a network of data aggregators, each data aggregator serves a set of data items at specific coherencies. Just as various fragments of a dynamic webpage are served by one or more nodes of a content distribution network, our technique involves decomposing a client query into subqueries and executing subqueries on judiciously chosen data aggregators with their individual subquery incoherency bounds. We provide a technique for getting the optimal set of subqueries with their incoherency bounds which satisfies client query's coherency requirement with least number of refresh messages sent from aggregators to the client. For estimating the number of refresh messages, we build a query cost model which can be used to estimate the number of messages required to satisfy the client specified incoherency bound. Performance results using real-world traces show that our cost-based query planning leads to queries being executed using less than one third the number of messages required by existing schemes.

Keywords: IEEE Project 2012, Data Mining Titles, Networking Titles, Cloud Computing, wireless Communcation.