Multi-Objective Adaptive Pigeon Inspired Optimization Algorithm Based Energy Efficient Routing In Wireless Sensor Network

Abstract

In recent years, Wireless Sensor Network (WSN) is considered as the main technologies which contains a huge number of sensor nodes for communication, sensing and computation abilities. Nowadays this network is used in many industrial and consumer applications such as monitoring and controlling industrial processes, mechanical health monitoring and military application. The main objective of WSN is to transfer the sensed data to destination using distributed sensor nodes. One of the main issues of WSN is limited energy of sensor nodes and high energy consumption. To avoid the problem, energy efficient routing protocol is introduced which consumes the energy during transmission and it can enhance the lifetime of the distributed sensor node. Therefore, in this chapter we focus on multi-objective routing on WSN using Adaptive Pigeon Inspired Optimization algorithm (APOA). In this approach, initially, the cluster heads (CH) are optimally selected using APOA. After the CH selection process, clusters are formed based on the distance between the remaining sensor nodes and CHs in communication region. Finally, trust-based routing is done. The proposed method is executed by NS2 simulator and performances are compared with existing methods such as Pigeon Optimization algorithm (POA), Particle swarm optimization (PSO) and genetic algorithm (GA) respectively. The performance metrics are delay, throughput, energy consumption, network lifetime, overhead and delivery ratio.