Sink mobility management in mobile sensor networks for cluster-heads load balancing

Paying attention to the limited battery energy of sensor nodes is one of the design challenges of wireless sensor networks (WSNs). It is essential to balance energy consumption to enhance network lifetime. In this research, we focus on clustering sensor nodes and optimizing the data transfer from the cluster head to the sink, which significantly reduces energy consumption. Furthermore, one of the most effective solutions to the critical problem of wireless sensor networks, known as the hotspot or energy-hole problem, is the use of a mobile sink. The proposed method employs two mobile sinks: one moves within a specific area, while the other traverses the entire network environment. Using the prioritized Random Way Point (RWP) mobility model, both mobile sinks select suitable locations in the network based on parameters such as density of nodes and cluster heads. To minimize frequent advertisements of the current location of the sinks, we have implemented location-aware cluster heads that save the updated positions of the two mobile sinks. The evaluation results indicate that the proposed method demonstrates higher efficiency compared to similar algorithms in terms of network lifetime, residual energy of nodes, number of sent packets, network coverage, and overhead. On average, the proposed method has shown an improvement of approximately 8% across all parameters .