An Energy Optimization Algorithm for UAV-Assisted Satellite Mobile Edge Computing System

In recent years, mobile edge computing (MEC) has become one of the most popular applications in the Internet of Things (IoT). With the help of satellite communications, MEC can be realized in remote areas. However, when transmitting directly to satellites, the energy consumption of IoT devices remains a challenge. This paper studies an unmanned aerial vehicle (UAV) assisted MEC system in which the UAV and satellite are both feasible MEC servers providing computation services. We aim to minimize the total energy consumption among all IoT devices by jointly determining the offloading decision and UAV's trajectory under the constraint of an energy budget. To tackle the problem, we utilize an existing heuristic algorithm for solving the classic Orienteering Problem and propose a dynamic programming algorithm to reduce the hovering cost of the UAV to serve more IoT devices. Simulation results show that the performance of the proposed algorithm is better than the baselines.