On Optimizing Mobile Charger Scheduling in Wireless Sensor Networks

Wireless rechargeable sensor networks (WRSNs) are widely used in many fields. However, the limited battery capacity of sensor nodes (SNs) prevents its development. To extend the battery life of SNs, they can be charged by a mobile charger (MC) equipped with radio frequency-based wireless power transfer (WPT). The paper addressed the issue of optimizing route planning and charging based on an MC with directional charging in on-demand networks. A mixed integer linear programming model (MILP) is proposed to obtain the appropriate stopping points (SPs) and orientation charging angles to respond to input requests in the shortest possible time and with minimum energy consumption. First, to select the SPs and the orientation charging direction, we utilize a clustering and discretization technique while minimizing the number of SPs and maximizing the charging cover. Then, to decrease the charging time of the required SNs as well as the MC’s energy consumption, we propose a heuristic search algorithm for adjusting the moving path for the directional mobile charger. Finally, experimental simulations are performed to evaluate the performance of the proposed directional charging scheduling algorithm, and the results reveal that the suggested approach outperforms existing studies in terms of MC energy consumption, charging delay, and distance traveled.