A novel joint optimization method based on mobile data collection for wireless rechargeable sensor networks

In wireless sensor networks, energy efficiency is a very critical issue as it impacts the network's lifetime and performance. Mobile data collection and wireless charging are two promising emerging techniques for enhancing energy efficiency. To achieve high charging rates and implement data collection with less energy consumption of sensors, we design a joint data collection and energy charging scheme by taking the strengths of these two techniques. The mobile charger is able to implement the energy charging and data collection simultaneously when it is equipped with the appropriate communication and charging hardware. We provide a two-step method for this joint problem. First, the topology is constructed by a novel clustering algorithm that aims to balance the number of clusters and the energy consumption of inter-cluster communication. Second, two modes of scheduling schemes are developed for facing the scenarios with different delay requirements (i.e., delay-tolerant scenario and delay-aware scenario) with heuristic algorithms. Compared with existing state-of-the-art methods, the simulation results present that our proposed scheduling schemes achieve the outperformance on packet delay and charging efficiency.

Duke Scholars

Author Peng Sun DKU Faculty