Efficient scheduling strategy for mobile chargers in task-based wireless sensor networks

Replenishing energy to wireless sensor networks is always a crucial problem as the energy capacity of sensor nodes is very limited. Scheduling mobile chargers to charge sensor nodes has been widely studied due to its efficiency and flexibility. However, most existing works focus on maximizing the charging utility or charging efficiency, which ignores the task performing functions of sensor nodes. In this paper, we study the problem of scheduling a mobile charger to maximize the task utility achieved by sensor nodes. We consider two different scenarios where sensor nodes are deployed on a line road and a ring road, respectively. We prove the NP-Hardness of our problems and design two approximation algorithms with guaranteed performance. We also investigate how to jointly schedule two mobile chargers in the line road scenario, and design a corresponding approximation algorithm to address the problem. We prove the approximation ratio of our algorithms through theoretical analysis, and conduct extensive simulations to validate the performance of our algorithms. Simulation results show that our algorithms always outperform the baselines, which demonstrates the effectiveness of our algorithms.