On-demand charging planning for WRSNs based on weighted heuristic method

In wireless rechargeable sensor networks, wireless energy transfer technology is considered as a key technique for increasing sensor lifespan. It is widely used to successfully supply electric energy to sensors via mobile charging device(s). However, one of the most difficult problems in such networks is determining an optimal charge-schedule for the mobile charging element to charge the sensors. Sensor residual energies, as well as their spatial-temporal limits and other network factors, all have an effect on the charge-schedule. To address this issue, this paper proposes a novel heuristic charging scheme aimed at maximising sensor lifetimes. A multi-node charger is used in the proposed scheme, which can receive and charge multiple sensors at the same time. The proposed scheme is real-time, dynamic and determines a near-optimal charge-schedule using a weighted heuristic method. As network parameters, the weight function includes requesting sensors’ residual energies, contribution-count values, and distances to charging element to quantify the sensors’ charging scheduling priorities. Finally, simulation studies demonstrate the charging efficacy of the proposed scheme, demonstrating that it outperforms existing ones in terms of life-success ratio and energy utility ratio.