摘要：Mobile Edge Computing (MEC), as a highly promising technology, effectively processes computation-intensive tasks by offloading them to edge servers. Utilizing the advantages of Unmanned Aerial Vehicles (UAVs) in deployment flexibility and broad coverage, UAV-assisted edge computing can significantly enhance system efficiency. This paper studies a scenario where a UAV-MEC system serves multiple Mobile Users (MUs) with random task arrivals and movements. We minimize the energy consumption of MUs by jointly optimizing UAV trajectory and resource allocation for MUs subjected to the UAV energy limit. The problem is formulated as a multi-stage Mixed-Integer Nonlinear Programming (MINLP) problem. To address this, we propose an algorithm called JTORA integrated Deep Reinforcement Learning (DRL) and Lyapunov optimization techniques. Specifically, we initially transform the multi-stage MINLP problem into a deterministic optimization problem utilizing Lyapunov techniques and decompose the original problem into two sub-problems in parallel. Through DRL, we solve the first sub-problem of trajectory and communication resources optimization. For the second sub-problem involving computing resource allocation, convex optimization is employed to get the optimal solution. Theoretical analysis and experimental results demonstrate that the JTORA algorithm can effectively reduce the energy consumption of MUs while ensuring UAV endurance.

关键字：Resource management; Autonomous aerial vehicles; Internet of Things; Trajectory optimization; Energy consumption; Edge computing; Servers; Stochastic processes; Heuristic algorithms; Computational modeling; Mobile edge computing (MEC); unmanned aerial vehicle (UAV); resource allocation; trajectory optimization; deep reinforcement learning (DRL)

ISSN号：1939-1374

卷、期、页：卷: 18期: 2页: 854-867

发表日期：2025-03-01

期刊分区（SCI为中科院分区）：二区

收录情况：SCI（科学引文索引印刷版）,EI（工程索引）,SCIE（科学引文索引网络版）

发表期刊名称：IEEE TRANSACTIONS ON SERVICES COMPUTING

参与作者：陈莹,杨耀宗,吴远,Zhao, Lian

第一作者：黄霁崴

论文类型：期刊论文

论文概要：陈莹,杨耀宗,吴远,黄霁崴,Zhao, Lian，Joint Trajectory Optimization and Resource Allocation in UAV-MEC Systems: A Lyapunov-Assisted DRL Approach，IEEE TRANSACTIONS ON SERVICES COMPUTING，2025，卷: 18期: 2页: 854-867

论文题目：Joint Trajectory Optimization and Resource Allocation in UAV-MEC Systems: A Lyapunov-Assisted DRL Approach