Task-oriented Energy Scheduling in Wireless Rechargeable Sensor Networks

Abstract

In recent years, the flourishing of Wireless Power Transfer (WPT) technology brings Wireless Sensor Networks (WSNs) a renewable, reliable, and controllable energy source. To achieve high efficiency, WPT and sensors both adopt directional antennas. Most previous works about directional charging optimize overall charging efficiency, but neglect energy scheduling on nodes for optimizing tasks. This disadvantage may cause a serious imbalance between the energy supply and task loads. This article takes both aspects into consideration. To achieve an overall performance improvement, we jointly schedule rotatable chargers and allocate tasks to nodes in a WSN powered by directional chargers. As far as we know, this is the first work to propose the Task-oriented Energy Scheduling (TOES) problem, i.e., given a set of rotatable directional chargers and some wireless rechargeable sensor nodes, scheduling chargers and nodes to maximize the total utility gained from a set of tasks. We prove the NP-Hardness of TOES. Then we design a 4-approximation algorithm for TOES by jointly solving two subproblems of the original one. We further extend this problem to the windowed task model and propose a \(\frac{4}{1-\gamma }\) approximation algorithm for it, where γ is the proportion of the rotating period. Finally, extensive simulation results show that our algorithms outperform baselines by at least 40.3%.