Debajit Sensarma

An Efficient Ant Based QOS Aware Intelligent Temporally Ordered Routing Algorithm for MANETS

A Mobile Ad hoc network (MANET ) is a self configurable network connected by wireless links. This type of network is only suitable for temporary communication linksas it is infrastructure-less and there is no centralised control. Providing QoS aware routing is a challenging task in this type of network due to dynamic topology and limited resources. The main purpose of QoS aware routing is to find a feasible path from source to destination which will satisfy two or more end to end QoS constrains. Therefore, the task of designing an efficient routing algorithm which will satisfy all the quality of service requirements and be robust and adaptive is considered as a highly challenging problem . In this work we have designed a new efficient and energy aware multipath routing algorithm based on ACO framework, inspired by the behaviours of biological ants. Basically by considering QoS constraints and artificial ants we have designed an intelligent version of classical Temporally Ordered Routing Algorithm(TORA) which will increase network lifetime and decrease packet loss and average end to end delay that makes this algorithm suitable for real time and multimedia applications.

A Novel Hierarchical ant Based QOS Aware Intelligent Routing Scheme for Manets

MANET is a collection of mobile devices with no centralized control and no pre-existing infrastructures. Due to the nodal mobility, supporting QoS during routing in this type of networks is a very challenging task. To tackle this type of overhead many routing algorithms with clustering approach have been proposed. Clustering is an effective method for resource management regarding network performance, routing protocol design, QoS etc. Most of the flat network architecture contains homogeneous capacity of nodes but in real time nodes are with heterogeneous capacity and transmission power. Hierarchical routing provides routing through this kind of heterogeneous nodes. Here, routes can be recorded hierarchically, across clusters to increase routing flexibility. Besides this, it increases scalability and robustness of routes. In this paper, a novel ant based QoS aware routing is proposed on a three level hierarchical cluster based topology in MANET which will be more scalable and efficient compared to flat architecture and will give better throughput.

Minimizing Boolean Sum of Products Functions Using Binary Decision Diagram

Two-level logic minimization is a central problem in logic synthesis, and has applications in reliability analysis and automated reasoning. This paper represents a method of minimizing Boolean sum of products function with binary decision diagram and with disjoint sum of product minimization. Due to the symbolic representation of cubes for large problem instances, the method is orders of magnitude faster than previous enumerative techniques. But the quality of the approach largely depends on the variable ordering of the underlying BDD. The application of Binary Decision Diagrams (BDDs) as an efficient approach for the minimization of Disjoint Sums-of-Products (DSOPs). DSOPs are a starting point for several applications.

The Reconstruction Conjecture

The Reconstruction Conjecture is one of the most engaging problems under the domain of Graph Theory. The conjecture proposes that every graph with at least three vertices can be uniquely reconstructed given the multiset of subgraphs produced by deleting each vertex of the original graph one by one. This conjecture has been proven true for several infinite classes of graphs, but the general case remains unsolved. In this paper we will outline the problem and give a practical method for reconstructing a graph from its node-deleted.

A Graph Theoretic Approach for Minimizing Storage Space using Bin Packing Heuristics

In the age of Big Data the problem of storing huge volume of data in a minimum storage space by utilizing available resources properly is an open problem and an important research aspect in recent days. This problem has a close relationship with the famous classical NP-Hard combinatorial optimization problem namely the “Bin Packing Problem” where bins represent available storage space and the problem is to store the items or data in minimum number of bins. This research work mainly focuses on to find a near optimal solution of the offline one dimensional Bin Packing Problem based on two heuristics by taking the advantages of graph. Additionally, extreme computational results on some benchmark instances are reported and compared with the best known solution and solution produced by the four other well-known bin oriented heuristics. Also some future directions of the proposed work have been depicted.

Data Hiding using Graphical Code based Steganography Technique.

Data hiding has received much attention due to rapid development of internet and multimedia technologies where security of information is a very important concern. This is achieved by Steganography, which is the art or science of hiding data into another data, so that human eyes cannot catch the hidden information easily. There are many ways to hide information-like inside an image, text, audio/ video etc. Among them image steganography is a very attractive research area. The goal is to transmit a data within a modified image (called stego-image)by minimizing the number of bit flips. In this paper, a new steganography technique has been proposed using Graphical codes and also comparison with steganography technique using BCH codes has been studied.