An Energy Efficient Artificial Neural Network based Clustering Protocol for Wireless Sensor Network

Wireless sensor nodes are equipped with compact batteries that supply the necessary energy for a several operational tasks in a wireless sensor network (WSNs). During the execution of these tasks, significant power is depleted from the sensor nodes (SNs). Nonetheless, given the restricted battery capacity of these SNs, they eventually become depleted, leading to the failure of individual nodes and compromising the integrity of the entire network. An essential aspect of addressing the challenge of energy depletion is the choice of the most suitable cluster head (CH). In this research paper, we proposed a model that employs an Artificial Neural Network (ANN) to designate a single node within each cluster as the $\mathbf{C H}$. This approach has resulted in the development of an energy-efficient clustering protocol, referred to as the Energy-Efficient Artificial Neural Network-Based Clustering Protocol (EEANNCP), tailored specifically for WSNs. Through extensive simulations, we have demonstrated that our proposed approach substantially enhances energy conservation and extends the network’s lifespan.