Adaptive, limited knowledge wireless recharging in sensor networks.

ABSTRACTWe investigate the problem of efficient wireless energy recharging in Wireless Rechargeable Sensor Networks (WRSNs). In such networks a special mobile entity (called the Mobile Charger) traverses the network and wirelessly replenishes the energy of sensor nodes. In contrast to most current approaches, we envision methods that are distributed, adaptive and use limited network information. We propose three new, alternative protocols for efficient recharging, addressing key issues which we identify, most notably (i) to what extent each sensor should be recharged (ii) what is the best split of the total energy between the charger and the sensors and (iii) what are good trajectories the MC should follow. One of our protocols (LRP) performs some distributed, limited sampling of the network status, while another one (RTP) reactively adapts to energy shortage alerts judiciously spread in the network. As detailed simulations demonstrate, both protocols significantly outperform known state of the art methods, while their performance gets quite close to the performance of the global knowledge method (GKP) we also provide, especially in heterogeneous network deployments.