Clustering and routing using spiral exploration mechanism with honey badger optimization in wireless sensor network

Abstract

Wireless sensor network (WSN) contains a huge number of spatially distributed sensor nodes that are connected by wireless to monitor and record information from the environment. The WSN nodes are battery-powered, thus reducing energy after a certain period which affects the network lifetime. To overcome this issue, this research proposed a spiral exploration mechanism with honey badger optimization (SEM-HBO) for cluster head (CH) and route path selection in WSN. The objective of this research is to reduce energy consumption and enhance network lifespan in WSN. The distance, communication cost, residual energy and cluster density are considered as fitness functions for selecting CH and route path in WSN. Through the SEM-HBO search behavior, it explores different routes and recognizes best one for reducing energy consumption and delays thereby enhancing network lifetime. The SEM-HBO performance is calculated based on packet delivery ratio (PDR), delay, energy consumption (EC), network lifetime (NL), and throughput for 100-500 nodes. The SEM-HBO performance is efficient and it achieves 99.62% and 99.59% of PDR for 100 and 200 nodes when compared to harmony search algorithm and competitive swarm optimization (HSA-CSO).