Chaotic Zebra Optimization Algorithm for Increasing the Lifetime of Wireless Sensor Network

Abstract

A wireless sensor network (WSN) is made up of one or more sink nodes, also known as base stations, and spatially dispersed sensors. Real-time monitoring of physical parameters like temperature, vibration, and motion is done using sensors, which also provide sensory data. A sensor node may act as a data router in addition to an originator of data. However, there are a number of issues with these sensors, including a high rate of energy consumption and a short network lifetime. One of the greatest ways to handle this problem is to use the clustering technique. In the WSN, selecting the optimal Cluster Heads (CHs) helps save energy consumption. Algorithms for Swarm Intelligence (SI) can assist in resolving challenging issues. We present a novel algorithm in this research to choose the top CHs in the WSN. A Chaotic Zebra Optimization Algorithm (CZOA) is the name of the new algorithm. We integrate the chaotic map and the zebra optimization algorithm (ZOA) in the CZOA. By doing so, the suggested algorithm’s processes of diversification can help to prevent the possibility of being trapped in local minima. Different SI algorithms are compared with the CZOA. The suggested algorithm’s results demonstrate that it can use less energy than the other algorithms and that more nodes are still alive for it than for the other algorithms combined. As a result, the CZOA demonstrated its superiority in lowering energy consumption and lengthening network lifetime.