Abstract

The recent breakthroughs in Wireless Power Transfer (WPT) facilitate supporting rechargeable sensors to enrich a series of energy-consuming applications. However, most charging scheduling schemes in rechargeable wireless sensor networks (WSNs) focus on sensing tasks instead of charging utility, which leaves a considerably high performance gap in the optimal result. Moreover, the charging scheduling is usually non-flexible, in which a full or nothing charging policy suffers from relatively low charging coverage as well as low efficiency. In this article, we focus on how to efficiently improve charging utility when introducing charging-oriented sensor placement and flexible scheduling policy. We formulate a general maximization optimization problem under a general routing constraint, which generates great difficulty. We utilize area partition and charging discretization methods to transform into the scope of maximizing a submodular function problem. Thus, a constant approximation algorithm is delivered to construct a near optimal charging tour. We analyze the performance loss from the discretization to guarantee that the output of the proposed algorithm has more than (1-ɛ)(1-1/ e )/4 of the optimal solution, where ɛ is an arbitrarily small positive parameter (0 < ɛ < 1). Both simulations and field experiments are conducted to evaluate the performance of our proposed algorithm.

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