Cluster Based Optimization of Routing in Distributed Sensor Networks Using Bayesian Networks with Tabu Search

Distributed Sensor Networks (DSNs) have attracted significant attention over the past few years. A growing list of many applications can employ DSNs for increased effectiveness especially in hostile and remote are as. In all application salargen umber of sensors are expected and requiring careful architecture and management of the net work. Grouping nodes in toclusters has been the most popular approach for support scalability in DSN. This paper proposes acluster based optimization of routing in DSN by employing a Bayesi an network (BN) with Tabu search (TS) approach. BN based approach is used to select efficient cluster head sand construction of BN for the proposed scheme. This approach in corporates energy level of each node, band width and link efficiency. The optimization of routing is considered as a design issue in DSN due to lack of energy consumption, delay and maximum time required for data transmission between source nodes (cluster heads) to sink node. In this work optimization of routing takes place through cluster head nodes by using TS. Simulations have been conducted to compare the performance of the proposed approach with LEACH protocol. The objective of the proposed work is to improve the performance of network in terms of energy consumption, through put, packet delivery ratio, and time efficiency of optimization of routing. The results hows that the proposed approach perform better than LEACH protocol that utilizes minimum energy, latency for cluster formation and reduce over head of the protocol.