arXiv subjects

Sabu M. Thampi

Publications and source records attributed to Sabu M. Thampi.

16 recordsLinked to original sources

arXiv2012

Survey on Distributed Data Mining in P2P Networks

The exponential increase of availability of digital data and the necessity to process it in business and scientific fields has literally forced upon us the need to analyze and mine useful knowledge from it. Traditionally data mining has used a data warehousing model of gathering all data into a central site, and then running an algorithm upon that data. Such a centralized approach is fundamentally inappropriate due to many reasons like huge amount of data, infeasibility to centralize data stored at multiple sites, bandwidth limitation and privacy concerns. To solve these problems, Distributed Data Mining (DDM) has emerged as a hot research area. Careful attention in the usage of distributed resources of data, computing, communication, and human factors in a near optimal fashion are paid by distributed data mining. DDM is gaining attention in peer-to-peer (P2P) systems which are emerging as a choice of solution for applications such as file sharing, collaborative movie and song scoring, electronic commerce, and surveillance using sensor networks. The main intension of this draft paper is to provide an overview of DDM and P2P Data Mining. The paper discusses the need for DDM, taxonomy of DDM architectures, various DDM approaches, DDM related works in P2P systems and issues and challenges in P2P data mining.

cs.DB↗

arXiv2011

An ACO Algorithm for Effective Cluster Head Selection

This paper presents an effective algorithm for selecting cluster heads in mobile ad hoc networks using ant colony optimization. A cluster in an ad hoc network consists of a cluster head and cluster members which are at one hop away from the cluster head. The cluster head allocates the resources to its cluster members. Clustering in MANET is done to reduce the communication overhead and thereby increase the network performance. A MANET can have many clusters in it. This paper presents an algorithm which is a combination of the four main clustering schemes- the ID based clustering, connectivity based, probability based and the weighted approach. An Ant colony optimization based approach is used to minimize the number of clusters in MANET. This can also be considered as a minimum dominating set problem in graph theory. The algorithm considers various parameters like the number of nodes, the transmission range etc. Experimental results show that the proposed algorithm is an effective methodology for finding out the minimum number of cluster heads.

cs.NI↗

arXiv2011

Securing Biometric Images using Reversible Watermarking

Biometric security is a fast growing area. Protecting biometric data is very important since it can be misused by attackers. In order to increase security of biometric data there are different methods in which watermarking is widely accepted. A more acceptable, new important development in this area is reversible watermarking in which the original image can be completely restored and the watermark can be retrieved. But reversible watermarking in biometrics is an understudied area. Reversible watermarking maintains high quality of biometric data. This paper proposes Rotational Replacement of LSB as a reversible watermarking scheme for biometric images. PSNR is the regular method used for quality measurement of biometric data. In this paper we also show that SSIM Index is a better alternate for effective quality assessment for reversible watermarked biometric data by comparing with the well known reversible watermarking scheme using Difference Expansion.

cs.CV↗

arXiv2010

Protocols for Bio-Inspired Resource Discovery and Erasure Coded Replication in P2P Networks

Efficient resource discovery and availability improvement are very important issues in unstructured P2P networks. In this paper, a bio-inspired resource discovery scheme inspired by the principle of elephants migration is proposed. A replication scheme based on Q-learning and erasure codes is also introduced. Simulation results show that the proposed schemes significantly increases query success rate and availability, and reduces the network traffic as the resources are effectively distributed to well-performing nodes.

cs.NI↗

arXiv2010

Survey of Search and Replication Schemes in Unstructured P2P Networks

P2P computing lifts taxing issues in various areas of computer science. The largely used decentralized unstructured P2P systems are ad hoc in nature and present a number of research challenges. In this paper, we provide a comprehensive theoretical survey of various state-of-the-art search and replication schemes in unstructured P2P networks for file-sharing applications. The classifications of search and replication techniques and their advantages and disadvantages are briefly explained. Finally, the various issues on searching and replication for unstructured P2P networks are discussed.

cs.NI↗

arXiv2010

An Enhanced Search Technique for Managing Partial Coverage and Free Riding in P2P Networks

This paper presents a Q-learning based scheme for managing the partial coverage problem and the ill-effects of free riding in unstructured P2P networks. Based on various parameter values collected during query routing, reward for the actions are computed and these rewards are used for updating the corresponding Q-values of peers. Thus, the routing is done through only nodes which have shown high performance in the past. Simulation experiments are conducted in several times and the results are plotted. Results show that the proposed scheme effectively manages free riders, generates high hit ratio, reduces network traffic and manages partial coverage problem.

cs.NI↗

arXiv2010

`Q-Feed' - An Effective Solution for the Free-riding Problem in Unstructured P2P Networks

This paper presents a solution for reducing the ill effects of free-riders in decentralised unstructured P2P networks. An autonomous replication scheme is proposed to improve the availability and enhance system performance. Q-learning is widely employed in different situations to improve the accuracy in decision making by each peer. Based on the performance of neighbours of a peer, every neighbour is awarded different levels of ranks. At the same time a low-performing node is allowed to improve its rank in different ways. Simulation results show that Q-learning based free riding control mechanism effectively limits the services received by free-riders and also encourages the low-performing neighbours to improve their position. The popular files are autonomously replicated to nodes possessing required parameters. Due to this improvement of quantity of popular files, free riders are given opportunity to lift their position for active participation in the network for sharing files. Q-feed effectively manages queries from free riders and reduces network traffic significantly

cs.NI↗

arXiv2009

Review of Replication Schemes for Unstructured P2P Networks

To improve unstructured P2P system performance, one wants to minimize the number of peers that have to be probed for the shortening of the search time. A solution to the problem is to employ a replication scheme, which provides high hit rate for target files. Replication can also provide load balancing and reduce access latency if the file is accessed by a large population of users. This paper briefly describes various replication schemes that have appeared in the literature and also focuses on a novel replication technique called Q-replication to increase availability of objects in unstructured P2P networks. The Q-replication technique replicates objects autonomously to suitable sites based on object popularity and site selection logic by extensively employing Q-learning concept.

cs.DC↗

arXiv2009

Introduction to Distributed Systems

Computing has passed through many transformations since the birth of the first computing machines. Developments in technology have resulted in the availability of fast and inexpensive processors, and progresses in communication technology have resulted in the availability of lucrative and highly proficient computer networks. Among these, the centralized networks have one component that is shared by users all the time. All resources are accessible, but there is a single point of control as well as a single point of failure. The integration of computer and networking technologies gave birth to new paradigm of computing called distributed computing in the late 1970s. Distributed computing has changed the face of computing and offered quick and precise solutions for a variety of complex problems for different fields. Nowadays, we are fully engrossed by the information age, and expending more time communicating and gathering information through the Internet. The Internet keeps on progressing along more than a few magnitudes, abiding end systems increasingly to communicate in more and more different ways. Over the years, several methods have evolved to enable these developments, ranging from simplistic data sharing to advanced systems supporting a multitude of services. This article provides an overview of distributed computing systems. The definition, architecture, characteristics of distributed systems and the various distributed computing fallacies are discussed in the beginning. Finally, discusses client/server computing, World Wide Web and types of distributed systems.

cs.DC↗

arXiv2009

Introduction to Bioinformatics

Bioinformatics is a new discipline that addresses the need to manage and interpret the data that in the past decade was massively generated by genomic research. This discipline represents the convergence of genomics, biotechnology and information technology, and encompasses analysis and interpretation of data, modeling of biological phenomena, and development of algorithms and statistics. This article presents an introduction to bioinformatics

cs.CE↗

arXiv2009

Swarm Intelligence

Biologically inspired computing is an area of computer science which uses the advantageous properties of biological systems. It is the amalgamation of computational intelligence and collective intelligence. Biologically inspired mechanisms have already proved successful in achieving major advances in a wide range of problems in computing and communication systems. The consortium of bio-inspired computing are artificial neural networks, evolutionary algorithms, swarm intelligence, artificial immune systems, fractal geometry, DNA computing and quantum computing, etc. This article gives an introduction to swarm intelligence.

cs.NE↗

arXiv2008

An Introduction to Knowledge Management

Knowledge has been lately recognized as one of the most important assets of organizations. Managing knowledge has grown to be imperative for the success of a company. This paper presents an overview of Knowledge Management and various aspects of secure knowledge management. A case study of knowledge management activities at Tata Steel is also discussed

cs.DB↗

arXiv2008

Mobile Agents for Content-Based WWW Distributed Image Retrieval

At present, the de-facto standard for providing contents in the Internet is the World Wide Web. A technology, which is now emerging on the Web, is Content-Based Image Retrieval (CBIR). CBIR applies methods and algorithms from computer science to analyse and index images based on their visual content. Mobile agents push the flexibility of distributed systems to their limits since not only computations are dynamically distributed but also the code that performs them. The current commercial applet-based methodologies for accessing image database systems offer limited flexibility, scalability and robustness. In this paper the author proposes a new framework for content-based WWW distributed image retrieval based on Java-based mobile agents. The implementation of the framework shows that its performance is comparable to, and in some cases outperforms, the current approach.

cs.DC↗

arXiv2008

Information Hiding Techniques: A Tutorial Review

The purpose of this tutorial is to present an overview of various information hiding techniques. A brief history of steganography is provided along with techniques that were used to hide information. Text, image and audio based information hiding techniques are discussed. This paper also provides a basic introduction to digital watermarking.

cs.CR↗

arXiv2007

A System for Predicting Subcellular Localization of Yeast Genome Using Neural Network

The subcellular location of a protein can provide valuable information about its function. With the rapid increase of sequenced genomic data, the need for an automated and accurate tool to predict subcellular localization becomes increasingly important. Many efforts have been made to predict protein subcellular localization. This paper aims to merge the artificial neural networks and bioinformatics to predict the location of protein in yeast genome. We introduce a new subcellular prediction method based on a backpropagation neural network. The results show that the prediction within an error limit of 5 to 10 percentage can be achieved with the system.

cs.NE↗

arXiv2007

Performance Comparison of Persistence Frameworks

One of the essential and most complex components in the software development process is the database. The complexity increases when the "orientation" of the interacting components differs. A persistence framework moves the program data in its most natural form to and from a permanent data store, the database. Thus a persistence framework manages the database and the mapping between the database and the objects. This paper compares the performance of two persistence frameworks ? Hibernate and iBatis?s SQLMaps using a banking database. The performance of both of these tools in single and multi-user environments are evaluated.

cs.DB↗