Joint Trajectory and Energy Consumption Optimization Based on UAV Wireless Charging in Cloud Computing System

Microwave Power Transfer (MPT) is a promising technology to charge sensor devices (SDs) wirelessly in wireless sensor networks, and Cloud Computing (CC) can significantly promote task processing capacity of SDs. However, the propagation loss can dramatically influence the harvested energy and computation performance. So, for wireless sensor networks, we study an unmanned aerial vehicle-assisted cloud wireless charging system with the cooperation of the cloud server and the unmanned aerial vehicle (UAV). First, the UAV acts as the energy transmitter, and we design a quantitative charging scheme according to the energy-aware of SDs' battery capacity. Second, the cloud server processes the tasks uploaded by SDs with the cooperation of the UAV, and we consider the communication connection between the cloud server and the UAV. Third, we propose the joint resource-trajectory optimization to reduce the energy consumption of UAVs. We put forward the Chaotically Adaptive Beetle Swarm Optimization Based on Cauchy Mutation (CABSOC) assisted block coordinate descent algorithm for addressing this non-convex problem. Numerical results indicate that the proposed solution can significantly improve the energy performance of the UAV. And the energy consumption is reduced by 11% compared with the solution with network function virtualization (NFV).