An efficient scheduling scheme for on-demand mobile charging in wireless rechargeable sensor networks

The wireless energy transfer (WET) technology has emerged as a new alternative to the energy problem of sensor nodes (SNs) and makes wireless rechargeable sensor networks (WRSNs) promising. The adoption of mobile charger (MC) for energy supply to the SNs via WET has attracted increasing attention in the recent years. However, determining the order by which SNs are replenished with energy (referred as charging scheduling problem) is a challenging issue due to spatial and temporal constraints. Therefore, an intelligent decision-making system such as fuzzy logic is entailed while determining the charging schedule of the SNs. Also, the fuzzy logic is very effective to deal with the uncertainties in the network. To this end, we propose a fuzzy logic based scheduling scheme for on-demand charging of the SNs. The proposed scheme blends different network parameters, such as residual energy, distance to MC, and critical node density to make decisions while scheduling the SNs. Through extensive simulation runs, we show that our scheme boosts the charging performance in contrast to state-of-theart methods in terms of energy usage efficiency, survival ratio, and average charging latency. The simulation results are also validated through the statistical test ANOVA and its subsequent post hoc analysis. (C) 2019 Elsevier B.V. All rights reserved.