Energy-efficient clustering-based mobile routing algorithm for wireless sensor networks

In this paper, we propose and investigate two types of algorithms for improving energy efficiency in wireless sensor networks. Clustering sensors in wireless sensor networks is considered an effective approach to prolonging network lifetime. In this paper, we divide the study area into clusters at 30-m2 intervals. In each cluster, the sensor that is the closest to the cluster center and has the highest residual energy is selected as the cluster head. In addition, a mobile sink is used to reduce the energy consumption of the cluster heads. The mobile sink travels to all clusters starting with the nearest cluster and collects data from the cluster heads. In the first model, cluster head selection is performed and the mobile sink route is calculated using a greedy approach. In the second model, cluster head selection is performed using an artificial neural network, and the mobile sink route is calculated using a greedy approach. We compared our models with the energy-efficient scalable routing algorithm by the first node dies parameter, all nodes die, and the residual energy of the network for each round condition. The simulation results demonstrated that the proposed models improved the energy efficiency and extended the network lifetime.