You Can Recharge With Detouring: Optimizing Placement for Roadside Wireless Charger

Wireless energy transfer technologies have played an important role in the development of Internet of Things. Most of the previous studies focus on scheduling mobile chargers efficiently for rechargeable sensor nodes. In this paper, we investigate the deployment problem for wireless charging stations (WCSs) in urban areas with respect to the users detouring cost when they move to the candidate WCSs. With pre-known user's trajectories and given number of WCSs, we deploy the WCSs to maximize the number of recharged users with guaranteed probability. We convert our deployment problem into an NP-hard weighted maximum coverage problem, and prove the objective function is a maximum submodular set function. To this end, a simple but efficient greedy algorithm with approximation factor of (1 - 1/ε) is proposed for the threshold detouring mode. In addition, an improved algorithm with an approximation factor of (1 - 1/√e) is presented for the linear/nonlinear detouring mode. Finally, we evaluate the performance of our algorithms by comparing them with two typical heuristic algorithms (flow-centric and random-based), and the impacts of different detouring thresholds on our algorithms by synthetic traces. Moreover, real trace-driven evaluations validate that our algorithm improves the coverage quality by 75% when compared to the two aforementioned algorithms.