Impact of Whale Optimization on CH Selection, Stability Region and Lifespan Expansion

Sensors are a vital part of any sensing network. The performance of a sensor node is influenced by its battery life. It has been proven that if batteries are placed in a remote or unsupervised area, they are impossible to replace. To improve battery life, it is essential to use an energy efficacious clustering technique. In this research paper, an optimal cluster head (CH) election strategy that relies on the whale optimization algorithm for a dense heterogeneous network (WOA-HN) is proposed. It employs a distinctive approach to CH election by incorporating multiple criteria, such as the leftover energy of nodes, the distance parameter, and the number of linked neighbor nodes. The WOA-HN algorithm's performance is evaluated using stability regions, network lifespan, and throughput. The proposed algorithm is compared to the LEACH, particle swarm optimization (PSO), and whale optimization algorithm (WOA-C), showing a performance boost in the stability region of 1318.51%, 113.60%, and 109.76%, network lifetime of 247.75%, 54.59%, and 33.71%, and further throughput of 1304.73%, 61.89%, and 37.62%, respectively.