Energy efficient chaotic sparrow search algorithm based clustering protocol for wireless sensor network communications

Abstract

Wireless sensor networks (WSN) include a collection of autonomous sensor nodes, which are generally deployed in a harsh or hostile environment to sense the physical parameters involved in the target region. It is highly utilized for target tracking, surveillance, and data gathering applications. Since the sensors in WSN operates on limited inbuilt batteries, it is needed to design energy efficient approaches to preserve energy and extend lifetime of the network. Earlier studies have reported that clustering is an effectual manner used for accomplishing energy efficiency and it is addressed with use of metaheuristic optimization algorithms. In this view, this paper present an energy efficient chaotic sparrow search algorithm based clustering (EE-CSSAC) technique for WSN. The proposed EE-CCSAC technique is dependent upon the integration of chaotic maps into the traditional sparrow search algorithm (SSA). In addition, the EE-CCSAC technique develops a fitness function with four variables to properly select the CHs and then organize clusters, thereby achieving energy efficiency. The experimental validation of the EE-CCSAC system takes place and the outcomes are related to recent clustering approaches. The simulation outcomes exhbited the effective outcome of the EE-CCSAC method on the other ones with respec to distinct estimation parameters.