Abstract

In recent years, Wireless Rechargeable Sensor Networks, which exploit wireless energy transfer technologies to address the energy constraint problem in traditional Wireless Sensor Networks, has emerged as a promising solution. There are two important factors that affect the performance of a charging process: charging path and charging time. In the literature, many studies have been done to propose efficient charging algorithms. However, most of the existing works focus only on optimizing the charging path. In this paper, we are the first one to jointly take into account both the charging path and charging time. Specifically, we aim at determining the optimal charging path and the charging time at each charging location to minimize the number of dead nodes. We first mathematically formulate the problem under mixed integer and linear programming. Then, we propose a periodic charging scheme, which is based on the Greedy and Genetic algorithm approaches. The experiment results show that our proposed the algorithm reduces significantly the number of dead nodes compared to a relevant benchmark.

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