Mobile Charging Sequence Scheduling for Optimal Sensing Coverage in Wireless Rechargeable Sensor Networks

In wireless rechargeable sensor networks (WRSNs), a novel approach to energy replenishment is offered by the utilization of mobile chargers (MCs), which charge nodes via transfer technology. However, previous research on charging schemes has commonly prioritized efficiency as performance index, neglecting importance quality sensing coverage (QSC). As network scale increases, MC’s power becomes unable meet needs all nodes, leading decline in QSC when nodes’ depleted. To solve this problem, we study problem sequence scheduling for optimal (MSSQ) and propose an improved quantum-behaved particle swarm optimization (IQPSO) algorithm. With attraction potential quantum space, algorithm will adaptively adjust contraction expansion coefficient iteratively, global solution sequence. Extensive simulation results demonstrate superiority IQPSO over widely used QPSO Greedy algorithms terms QSC, especially large-scale networks.