Stochastic Mobile Energy Replenishment and Adaptive Sensor Activation for Perpetual Wireless Rechargeable Sensor Networks

Recent studies have shown that environmental energy harvesting technologies have the potential to provide perpetual operation to wireless sensor networks. However, due to the large variations of the ambient energy source, such networks could only support low-rate data services and the performance is affected by many unpredictable environmental factors. To deliver energy to sensor nodes reliably, in this paper, we apply the novel wireless power transmission technology to rechargeable sensor networks by introducing a mobile actuator to replenish sensor energy wirelessly. We first establish an analytical model based on stochastic wireless energy replenishment to obtain a variety of performance metrics. Then based on the theoretical results, we further propose battery-aware mobile energy replenishment scheme and present two heuristic algorithms: (1) linear adaptation sensor activation with prioritized recharge; and (2) battery-aware activation with selective recharge. We validate the theoretical results and evaluate the performance of the proposed algorithms through extensive simulations. The results demonstrate that a good design of sensor activation with effective control of mobile energy replenishment can provide substantial performance improvement.