Energy–Latency Tradeoff for Computation Offloading in UAV-Assisted Multiaccess Edge Computing System

Unmanned aerial vehicles (UAVs) have been considered as a promising approach for providing additional computation capability and extensive coverage to ground mobile devices (MDs), especially in the scenario where the communication infrastructure is unavailable. This article investigates a UAV-assisted multiaccess edge computing system, where a number of ground MDs are served by a flying UAV and a ground base station, both of them are equipped with computation resources. The system aims to minimize the weighted cost of time latency and energy consumption, subject to the constraints on offloading decisions and resource competition. Since this problem is NP-hard, and the MDs are autonomous, we propose a game theory-based scheme to find the optimal solution and prove the existence of the Nash equilibrium. Meanwhile, we propose another two schemes as the benchmark to evaluate the efficiency and effectiveness of the game-theoretic solution. The simulation results show that the game-theoretic scheme is able to achieve a near-optimal performance, and the convergence time is also stable when the number of MDs increases.