Collaborative computation offloading and trajectory planning in locally observable multi-UAV MEC networks

IF 4.4 2区 计算机科学 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE
Yuan He , Xie Jun , Yaqun Liu , Xijian Luo
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引用次数: 0

Abstract

Unmanned Aerial Vehicles (UAVs) can be deployed as aerial edge servers to provide ground users with mobile edge computing (MEC) services in a collaborative manner. In this paper, we investigate the motion and computation decision-making problem of the multi-UAV-assisted MEC in a locally observed environment. Firstly, a multi-UAV-assisted MEC network model is proposed taking into account the collaborative computation among UAVs and the task’s queuing delay. Secondly, we propose a reinforcement learning algorithm based on Graph Attention Networks (GAT) named GatPPO to implement UAV control based on local information. The local networks observed by UAVs are abstracted into heterogeneous and homogeneous graphs. Then, we extract and aggregate the graphs’ features with GAT to alleviate the problem of inconsistent input dimensions caused by the number of neighbors and users changing. In addition, two actor-critic networks are designed in each UAV agent for the trajectory planning and computation decisions respectively to solve the problem of asynchronous actions selection due to different frequencies. The numerical simulation results show that compared with the benchmark algorithms, GatPPO reduces the computation delay by about 10 %–30 % and improves user satisfaction by about 113 % at most when a single UAV has limited computing resources.
局部可观测多无人机MEC网络协同计算卸载与轨迹规划
无人机(uav)可以部署为空中边缘服务器,以协作方式为地面用户提供移动边缘计算(MEC)服务。本文研究了局部观测环境下多无人机辅助MEC的运动和计算决策问题。首先,考虑无人机之间的协同计算和任务的排队延迟,提出了多无人机辅助的MEC网络模型;其次,提出了一种基于图注意网络(GAT)的强化学习算法GatPPO,实现了基于局部信息的无人机控制。将无人机观测到的局部网络抽象为异构图和同构图。然后,我们利用GAT对图的特征进行提取和聚合,以缓解由于邻居数量和用户数量的变化而导致的输入维度不一致的问题。此外,在每个无人机智能体中设计了两个行为批判网络,分别用于轨迹规划和计算决策,以解决不同频率下的异步动作选择问题。数值仿真结果表明,在单架无人机计算资源有限的情况下,与基准算法相比,GatPPO算法的计算延迟最多减少10% ~ 30%,用户满意度最多提高113%左右。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Computer Networks
Computer Networks 工程技术-电信学
CiteScore
10.80
自引率
3.60%
发文量
434
审稿时长
8.6 months
期刊介绍: Computer Networks is an international, archival journal providing a publication vehicle for complete coverage of all topics of interest to those involved in the computer communications networking area. The audience includes researchers, managers and operators of networks as well as designers and implementors. The Editorial Board will consider any material for publication that is of interest to those groups.
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