Improved EPOA clustering protocol for lifetime longevity in wireless sensor network

Abstract

Wireless Sensor Networks (WSNs) are determined to be the hottest domain that gained more attention due to their suitability and applicability in modern applications that include environment monitoring, disaster management, and medical care observation. These WSNs possess a shorter lifetime due to the restricted energy in the non-rechargeable battery present in the sensor nodes. Moreover, bandwidth is the herculean challenge in WSNs due to the significant influence on the communication cost introduced due to the power consumption of sensor nodes. At this juncture, clustering is proven to be the best strategy that could be optimally utilized to conserve energy in WSNs. In this paper, Improved Emperor Penguin Optimization Algorithm-based Clustering Protocol (IEPOACP) is propounded for extending network lifespan with maximized energy stability. This IEPOACP is designed to select optimal sensor nodes as CHs through the exploration and exploitation phases that mimic the huddling characteristics of emperor penguins. It adopted the process of generating and estimating the huddle boundary, huddle temperature profile, distance estimation between search agents, and effective mover relocation process for the CHs selection process. The performance of the proposed IEPOACP attained better energy efficiency and network lifetime of 35%, 58%, and 67% compared to the competitive CH selection approaches used for comparison.