  In wireless rechargeable sensor networks (WRSNs), most of researches address
energy scarcity by introducing one or multiple ground mobile vehicles to
recharge energy-hungry sensor nodes. The charging efficiency is limited by the
moving speed of ground chargers and rough environments, especially in
large-scale scenarios or challenging scenarios such as separate islands. To
address the limitations, some researchers consider replacing ground mobile
chargers with lightweight unmanned aerial vehicles (UAVs) to support extremely
large-scale scenarios, because of the UAV moving at higher speed without
geographical limitation. Moreover, multiple automatic landing wireless charging
PADs are deployed in the network to recharge UAVs automatically. In this work,
we investigate the problem of introducing the minimal number of PADs in
UAV-based WRSNs. We propose a novel and adaptive PAD deployment scheme named
CDC & DSC that can adapt to arbitrary locations of the base station, arbitrary
geographic distributions of sensor nodes, and arbitrary sizes of network areas.
In the proposed scheme, we first obtain an initial PAD deployment solution by
clustering nodes in geographic locations. Then, we propose a center shift
combining algorithm to optimize this solution by shifting the location of PADs
and attempting to merge the adjacent PADs. The simulation results show that
compared to existing algorithms, our proposed scheme can use fewer PADs to
charge the whole network.
