A New Dynamic Energy-Based Clustering Model For Wireless Sensor Networks

since sensor nodes have limited energy resources, prolonging network lifetime and improving capability are essential elements in energy-efficient Wireless Sensor Networks (WSNs). Most existing approaches consider the residual energy of a single node when electing a cluster head (CH), omitting other factors associated with the node, thus, this paper proposes a new scheme energy-based clustering model (EBCM) for WSNs to reduce the overall energy consumption, balance the energy consumption among all nodes and improve the network stability. Based on the LEACH, EBCM take into consideration node's current energy and degree in clustering process, the study has examined the performance of the proposed EBCM algorithm using simulation experiments. We compare the performance of our EBCM against some counterparts. The results demonstrate that our algorithm outperforms its counterparts in terms of energy efficiency and stability.