Optimal cluster head selection for energy efficient wireless sensor network using hybrid competitive swarm optimization and harmony search algorithm

Abstract

A Wireless Sensor Network (WSN) is a network made up of many sensor nodes that are geographically dispersed. Because the sensor nodes in WSN are battery-powered, energy efficiency is a major issue. As a result, it is critical to make effective use of available energy in order to avoid energy waste. The clustering system provides an energy-efficient method of data transfer. The existing clustering scheme utilises distinctive Low-Energy Adaptive Clustering Hierarchy (LEACH) and optimization approaches faces issues like complicated local search, trade off in exploration and exploitation. A combination of the Harmony Search Algorithm (HSA) and the Competitive Swarm Optimization (CSO) is developed for energy efficient selection of cluster head (CH) to provide a global search with quick convergence rate. The proposed method has a high HSA search efficiency and a dynamic CSO capability that extends the life of sensor nodes. The proportion of alive nodes, count of dead nodes, residual energy and throughput are used to measure the hybrid algorithm's performance. In terms of throughput and residual energy, the suggested hybrid HSA-CSO algorithm surpasses the current methods.