Energy Adaptive Collaborative Charging Scheduling for Wireless Rechargeable Sensor Networks

In this paper, we propose a dynamic collaborative charging scheduling mechanism with energy adaptability. This mechanism integrates periodic and on-demand charging scheduling, improving the charging stability and the energy adaptability of the network. We first construct the network core sensor nodes based on the Minimum Connected Dominating Set (MCDS), determine the data forwarding route, and design the evaluation method of the sensor node importance weight based on it. Next, we use the hierarchical clustering algorithm to establish the charging groups based on the network topology, and determine the collection of the sensor nodes that can be charged simultaneously, improving the rationality of the charging locations. Next, we design a hybrid algorithm of the mean-shift and hierarchical clustering algorithm to cluster the charging groups into the charging zones, which ensures the compactness of the sensor nodes in each charging zone and the balance of the charging load distribution. On this basis, we design an integration mechanism of periodic and on-demand charging scheduling: when the sensor nodes are in a state of high residual energy, we implement periodic zonal collaborative charging scheduling according to the charging groups and the charging zones to ensure the stability of the network performance; Otherwise, we build a hybrid charging priority allocation mechanism based on the sensor node importance weight and remaining survival time and implement on-demand competitive collaborative charging scheduling according to it, which ensures the energy adaptability of the charging process and reduces the network performance degradation rate. Finally, we have verified the performance advantages of our work through a large number of simulations.