Cluster Head Selection in Wireless Sensor Network using Energy-Efficient Grey Wolf Optimization (MEEGWO)

Abstract

Researchers in the field of telecommunications have long been interested in Wireless Sensor Networks (WSNs). Wide-area sensor networks (WSNs) are formed by large numbers of sensor nodes that combine sensing, processing, and wireless communication capabilities. Sensing systems that monitor and control physical and environmental processes frequently use these networks. Nevertheless, the lengthy operating lifespan of WSNs is sometimes limited by the high energy consumption of network nodes, which is a major difficulty in the field In this study, MATLAB was utilized as a simulation platform to evaluate and contrast the efficiency with which three protocols for wireless sensor networks optimize energy consumption: the Fuzzy Protocol, Energy Efficient Grey Wolf Optimization (MEEGWO), and Modified Low-energy Adaptive Clustering Hierarchy (MLEACH). The simulations focused on assessing the number of active sensor nodes and evaluating the network's lifespan by measuring the percentage of nonoperational (dead) nodes, which are critical metrics for determining protocol effectiveness. Results indicated that MEEGWO outperformed both Fuzzy and MLEACH protocols. Here survivability of MEEGWO is 25% more than Fuzzy and 27% more than MLEACH and number of dead node are more increase as number of rounds are increase in Fuzzy and MLEACH whereas number of dead nodes in less in MEEGWO, it perform more well in 1300 round to 1700 rounds .