Towards Maximizing Coverage of Targets for WRSNs by Multiple Chargers Scheduling

In recent years, wireless rechargeable sensor networks (WRSNs) have gained significant attention in the research community due to the current advancements in wireless power transfer technology. In mobile charger scheduling, previous works primarily emphasized the survival rate of sensor nodes. However, the primary task of a WRSN is to monitor targets in a given area. Therefore, the coverage of targets (CoT) maximization should be the primary objective of mobile charger scheduling. In this paper, we shift the focus to the CoT maximization on-demand charging scheduling problem, and formulate it as a multi-objective optimization problem, aiming to simultaneously enhance the average coverage and energy efficiency. We prove that the problem is NP-hard by reformulating it as a Multiple Travelling Salesman Problem with Deadline. We first propose the multiple chargers scheduling scheme for maximizing coverage of targets called MaxCov, which is designed to optimize the charging scheduling process and improve network performance in terms of coverage. Then, we further propose the multiple chargers scheduling scheme based on requests grouping called MaxCov-RG, which can well balance the trade-off between the performance and computational complexity. Finally, we validate the effectiveness of the proposed schemes via extensive simulations.