Edinburgh Napier University

  Since sensor nodes have limited energy resources, prolonging network lifetime and improving scalability 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, such as its location within hte WSN topology and its nodal degree. Thus, this paper proposes a new Dynamic Weight Clustering based Algorithm (DWCA) for WSNs to reduce the overall energy consumption, balance the energy consumption among all noces and improve the network scalability. The study has examined the performance of the proposed DWCA algorithm using simulation experiments. We copare the performance of our DWCA against some counterparts. The results demonstrate that our algorithm outperforms its counterparts in terms of energy efficiencey and scalability.