A METAHEURISTC SWARM BASED APPROACH FOR THE OPTIMIZATION OF ENERGY EFFICIENT NETWORK LIFETIME IN WIRELESS SENSOR NETWORKS

Abstract

This paper focuses on the implementation of Nature inspired metaheuristic algorithms in Wireless Sensor Networks (WSNs) such as Particle Swarm Optimization (PSO), Whale Optimization Algorithm (WOA) can be implemented in WSNs. The performance is evaluated on Network Lifetime, Clustering of nodes, energy consumption levels. It is observed that the PSO and WOA are consistently shows better results than Low-Energy Adaptive Clustering Hierarchy (LEACH). However, The WOA have been competitive with the PSO algorithm with its results leaning towards on the better side. The study complements related research on the application of swarm intelligence in WSN by focusing on routing optimization, energy aware protocols and centralized clustering of nodes.