An Adaptive Charging Planning Scheme based on Node Movement Prediction in Wireless Rechargeable Sensor Networks

Wireless rechargeable sensor networks (WRSNs) can prolong the lifetime of wireless sensor networks by introducing static or mobile chargers to recharge the energy-hungry sensor nodes. Most of the existing research on WRSNs with static chargers assumes that the energy of chargers is unlimited and focuses on selecting specific locations to deploy chargers. However, in the actual scenario, it is difficult to ensure that the static charger has a continuous and stable energy supply, so this assumption does not hold. Therefore, there is a trade-off between the energy obtained by the nodes and the energy consumed by the static chargers. For the WRSNs with non-deterministic mobile nodes, it is more important to balance this trade-off due to the uncertainty of node movement. To address this problem, an adaptive charging scheme based on node movement prediction is proposed in this paper. In the proposed scheme, once a node moves into the communication range of a static charger, the charger predicts the node's trajectory within the communication coverage based on the node's historical trajectory; then it customizes a charging plan for the node based on the prediction result to save charging energy by adjusting its charging output power to complete the energy replenishment of the node according to the relative distance between the node and the charger. Simulation results show that the proposed scheme can better balance the trade-off between the energy gained by the nodes and the energy consumed by the static chargers compared with existing algorithms.