This paper studies the problem of Radiation cOnstrained scheduling of wireless Charging tasKs (ROCK), that is, given wireless charging tasks with required charging energy and charging deadline for rechargeable devices, scheduling the power of wireless chargers to maximize the overall effective charging energy for all rechargeable devices, and further to minimize the total charging time, while guaranteeing electromagnetic radiation (EMR) safety, i.e., no point on the considered 2-D area has EMR intensity exceeding a given threshold. To address ROCK, we first present a centralized algorithm. We transform ROCK from nonlinear problem to linear problem by applying two approaches of area discretization and solution regularization, and then propose a linear programming-based greedy test algorithm to solve it. We also propose a distributed algorithm that is scalable with network size by presenting an area partition scheme and two approaches called area-scaling and EMR-scaling, and prove that it achieves effective charging energy no less than (1- ε) of that of the optimal solution, and charging time no more than that of the optimal solution. We conduct both simulation and field experiments to validate our theoretical findings. The results show that our algorithm achieves 94.9% of the optimal effective charging energy and requires 47.1% smaller charging time compared with the optimal one when ε ≥ 0.2, and outperforms the other algorithms by at least 350.1% in terms of charging time with even more effective charging energy.

Wireless Power Transfer (WPT) technology has witnessed huge development because of its convenience and reliability. This paper concerns the fundamental issue of wireless charger PLacement with Optimized charging uTility (PLOT), that is, given a fixed number of chargers and a set of points on the plane, determining the positions and orientations of chargers such that the overall expected charging utility for all points is maximized. To address PLOT, we propose a 1 - 1/e - ε approximation algorithm. First, we present techniques to approximate the nonlinear charging power and the expected charging utility to make the problem almost linear. Second, we develop a Dominating Coverage Set extraction method to reduce the continuous search space of PLOT to a limited and discrete one without performance loss. Third, we prove that the reformulated problem is essentially maximizing a monotone submodular function subject to a matroid constraint, and propose a greedy algorithm to address this problem. We conduct both simulation and field experiments to validate our theoretical results, and the results show that our algorithm can outperform comparison algorithms by at least 46.3%.

This paper studies the problem of Radiation cOnstrained scheduling of wireless Charging tasKs (ROCK), that is, given wireless charging tasks with required charging energy and charging deadline for rechargeable devices, scheduling the power of wireless chargers to maximize the overall effective charging energy for all rechargeable devices, and further to minimize the total charging time, while guaranteeing electromagnetic radiation (EMR) safety, i.e., no point on the considered 2D area has EMR intensity exceeding a given threshold. To address ROCK, we first present a centralized algorithm. We transform ROCK from nonlinear problem to linear problem by applying two approaches of area discretization and solution regularization, and then propose a linear programming based greedy test algorithm to solve it. We also propose a distributed algorithm by presenting an area partition scheme and two approaches called area-scaling and EMR-scaling, and prove that it achieves effective charging energy no less than (1 -- ϵ) of that of the optimal solution, and charging time no more than that of the optimal solution. We conduct both simulation and field experiments to validate our theoretical findings. The results show that our algorithm achieves 94.9% of the optimal effective charging energy and requires 47.1% smaller charging time compared with the optimal one when ϵ ≥ 0.2, and outperforms the other algorithms by at least 350.1% in terms of charging time with even more effective charging energy.

As battery-powered mobile devices become more popular and energy hungry, wireless power transfer technology, which allows the power to be transferred from a charger to ambient devices wirelessly, receives intensive interests. Existing schemes mainly focus on the power transfer efficiency but overlook the health impairments caused by RF exposure. In this paper, we study the safe charging problem (SCP) of scheduling power chargers so that more energy can be received while no location in the field has electromagnetic radiation (EMR) exceeding a given threshold Rt. We show that SCP is NP-hard and propose a solution, which provably outperforms the optimal solution to SCP with a relaxed EMR threshold (1-ε)Rt. Testbed results based on 8 Powercast TX91501 chargers validate our results. Extensive simulation results show that the gap between our solution and the optimal one is only 6.7% when ε = 0.1, while a naive greedy algorithm is 34.6% below our solution.