Route Optimization and Optimal Cluster Head Selection for Cluster-Oriented Wireless Sensor Network Utilizing Circle-Inspired Optimization Algorithm

Abstract

Abstract A wireless sensor network (WSN)'s lifespan and optimal orientation are greatly increased by clustering. Clustering selects non-cluster heads (NCHs) and cluster heads (CHs) and integrates sensor nodes via clusters. The purpose of this research is to find the best route and select the best cluster head for the WSN with the help of optimization methodology. The adaptive multi-path routing protocol (AMPRP), which is best chosen utilizing the circle-inspired optimization algorithm (CIOA) algorithm, is proposed in this study as a method for choosing NCHs and CHs. The optimal CHs have been chosen after the probabilities have been calculated, and the findings have been utilized to identify the optimal shortest path employing the same CIOA. To find the best route, the CIOA algorithm employs a fitness function made out of a network. The superiority of the proposed model is demonstrated by validating it with various state-of-the-art methods in terms of distinct analysis. The proposed AMPRP-CIOA for the optimal route and CH selection model in terms of energy consumption is 85.71%, 86.67%, 88.89%, and 77.78% better than EAHPW-TOPSIS, DA-EECHS, GEEC, and EADCR, respectively.