Static and mobile target k-coverage in wireless rechargeable sensor networks

Energy remains a major hurdle in running computation-intensive tasks onwireless sensors. Recent efforts have been made to employ aMobile Charger (MC) to deliver wireless power to sensors, which provides a promising solution to the energy problem.Most of previousworks in this area aim atmaintaining perpetual network operation at the expense of high operating cost ofMC. In themeanwhile, it is observed that due to the lowcost ofwireless sensors, they are usually deployed at high density so there is abundant redundancy in their coverage in the network. For such networks, it is possible to take advantage of the redundancy to reduce the energy cost. In this paper, we relax the strictness of perpetual operation by allowing some sensors to temporarily run out of energy while stillmaintaining target k-coverage in the network at lower cost ofMC.We first establish a theoreticalmodel to analyze the performance improvements under this new strategy. Then, we organize sensors into load-balanced clusters for targetmonitoring by a distributed algorithm. Next,we propose a charging algorithmnamed λ-GTSPCharging Algorithm to determine the optimal number of sensors to be charged in each cluster tomaintain k-coverage in the network and derive the route forMC to charge them.We further generalize the algorithmto encompassmobile targets aswell. Our extensive simulation results demonstrate significant improvements of network scalability and cost saving thatMCcan extend charging capability over 2-3 timeswith a reduction of 40 percent ofmoving cost without sacrificing the network performance.