WSN Cluster Routing Method Based on Improved Whale Optimization Algorithm

Abstract

Abstract To address the energy consumption issue in the cluster routing protocol of the wireless sensor network (WSN), a Whale Optimization Algorithm based on Nonlinear factors and Chaotic mapping (NC-WOA) is designed. This improves the quality of the initial population, enhancing the algorithm's capacity for global exploration and escaping local optima. Furthermore, an Efficient Distributed and Energy-Saving Clustering Routing Algorithm (EDESC) is designed based on the NC-WOA algorithm. Factors of node energy, node distance, and node density are incorporated into the threshold function, applying NC-WOA in the cluster head selection stage. Simulation results demonstrate that the performance of the NC-WOA surpasses that of other algorithms. In terms of the number of rounds for the half of the nodes to die, compared to the Distributed High-Efficiency Entropy Energy-Saving Cluster Routing Algorithm (DHEEC) and the Distributed Energy-Efficient Clustering with Firefly Algorithm (DEEC-FA), EDESC showed an improvement of 27.45% and 47.81%, respectively. The energy utilization ratio is enhanced by 16.63% compared to DHEEC and by 83.32% compared to DEEC-FA.