Secure and Energy Aware Cluster based Routing using Trust Centric – Multiobjective Black Widow Optimization for large scale WSN

Abstract

Wireless Sensor Network (WSN) is a promising approach that is developed for a wide range of applications due to its low installation cost. However, the nodes in the WSN are susceptible to different security threats, because these nodes are located in hostile or harsh environments. Moreover, an inappropriate selection of routing path affects the data delivery of the WSN. The important goal of this paper is to obtain secure data transmission while minimizing energy consumption. In this paper, Trust Centric - Multiobjective Black Widow Optimization (TC-MBWO) is proposed for selection of Secure Cluster Head (SCH) from the large-scale WSN. Moreover, the secure routing path is generated by using the TC-MBWO, in which the factors considered for the cost function are: residual energy, distance, trust and node degree. Therefore, the secured clustering and routing achieved by using TC-MBWO, provides the resistance against malicious nodes and simultaneously the energy consumption is also minimized by identifying the shortest path. The proposed TC-MBWO method is analyzed in terms of alive nodes, dead nodes, energy consumption, throughput, and network lifetime. Here, the TC-MBWO method is compared with different existing methods such as Low Energy Adaptive Clustering Hierarchy (LEACH), Particle Swarm Optimization - Grey Wolf Optimizer (PSO-GWO), Particle-Water Wave Optimization (P-WWO) and Particle-based Spider Monkey Optimization (P-SMO). The alive nodes of the TC-MBWO are 70 for 2800 rounds which are higher in number when compared to the PSO-GWO, P-WWO and P-SMO.