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Joint power charging and routing in wireless rechargeable sensor networks

Research output: Contribution to journalArticle

Jie Jia, Jian Chen, Yansha Deng, Xingwei Wang, Hamid Aghvami

Original languageEnglish
Article number2290
JournalSensors (Switzerland)
Issue number10
Early online date9 Oct 2017
Publication statusE-pub ahead of print - 9 Oct 2017


King's Authors


The development of wireless power transfer (WPT) technology has inspired the transition from traditional battery-based wireless sensor networks (WSNs) towards wireless rechargeable sensor networks (WRSNs). While extensive efforts have been made to improve charging efficiency, little has been done for routing optimization. In this work, we present a joint optimization model to maximize both charging efficiency and routing structure. By analyzing the structure of the optimization model, we first decompose the problem and propose a heuristic algorithm to find the optimal charging efficiency for the predefined routing tree. Furthermore, by coding the many-to-one communication topology as an individual, we further propose to apply a genetic algorithm (GA) for the joint optimization of both routing and charging. The genetic operations, including tree-based recombination and mutation, are proposed to obtain a fast convergence. Our simulation results show that the heuristic algorithm reduces the number of resident locations and the total moving distance. We also show that our proposed algorithm achieves a higher charging efficiency compared with existing algorithms.

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