Joint Trajectory Design and Resource Allocation in UAV-Enabled Heterogeneous MEC Systems

This article considers a heterogeneous mobile-edge computing (HMEC) system with multiple energy-limited Internet of Things (IoT) devices and an unmanned aerial vehicle (UAV). The UAV can supply energy to all the IoT devices through wireless power transfer. To maximize the utilization of the communication and computation resources, all the IoT devices are divided into two groups, i.e., the active devices and the idle devices. The UAV and the idle devices assist the active devices in executing computing tasks. We formulate an optimization problem that maximizes the minimum task computation data volume among all the active devices by jointly optimizing the UAV trajectory and the communication and computation resource allocation. Since the problem is nonconvex, we decompose the problem into two subproblems: 1) the UAV trajectory design and the computation resource allocation and 2) the time allocation. We utilize a block coordinate descent approach to solve these two subproblems alternately. Simulation results demonstrate that the proposed algorithm can provide an optimized trajectory robust to different initializations. Additionally, compared to the benchmark algorithms, our proposed algorithm shows superior performance in terms of system efficiency and computation data volume.