Charging Oriented Sensor Placement and Flexible Scheduling in Rechargeable WSNs

The recent breakthrough in Wireless Power Transfer (WPT) provides a promising way to support rechargeable sensors to enrich a series of energy-consuming applications. Unfortunately, two major design restrictions hinder the applicability of rechargeable sensor networks. First, most of the sensor placement schemes are focusing on the sensing tasks instead of the charging utility, which leaves a considerably high performance gap towards the optimal result. Second, the charging scheduling is non-flexible, where full or nothing charging policy suffers from the relatively low charging coverage as well as efficiency. In this paper, we focus on how to efficiently improve the charging utility when introducing charging oriented sensor placement and flexible scheduling policy. To this end, we jointly consider optimizing node positions and charging allocations. In particular, we formulate a general convex optimization problem under a general routing constraint, which generates great difficulty. We utilize area partition and charging discretization methods to reformulate a submodular function maximization problem. Thus a constant approximation algorithm is delivered to construct a near optimal charging tour. To this end, we analyze the performance loss from the discretization to guarantee that the output of the proposed algorithm has more than $(1 -\varepsilon)/4 (1 - 1 /e)$ of the optimal solution, where $\varepsilon$ is an arbitrarily small positive parameter $(0 \leq \varepsilon \leq 1)$. Both simulations and field experiments are conducted to evaluate the performance of our proposed algorithm.