Improved Cluster Head Selection Using Particle Swarm Optimization and Neural Network in WSN

Due to the advancement of technologies, Wireless Sensor Network (WSN) is applied in every field due to its huge advantages. A thousand sensors are connected to provide better quality information based on application. In this proposal, the author examines the Low-Energy Adaptive Clustering Hierarchy (LEACH) protocol for efficient information transmission. It is an energy-efficient protocol designed to prolong the lifetime of the network by reduction of energy consumption. The Particle Swarm Optimization Algorithm with Artificial Neural Network is introduced to optimize the LEACH routing protocol, and is used to identify the optimal route under two different scenarios; with Particle Swarm Optimization (PSO) plus Artificial Neural Network (ANN), and without PSO+ANN. The performance of the presented approach is evaluated in terms of comparative analysis of throughput (kbps), Energy Consumption (joules), delay (ms), Packet Delivery Ratio (PDR), and Number of alive nodes. The simulation results evaluation describes that PSO + ANN provides better results as compared to without PSO +ANN approach.