数据采集与处理2024，Vol.39Issue(6)：1432-1444,13.DOI:10.16337/j.1004-9037.2024.06.012
基于数据压缩的无人机边缘计算卸载优化
Offloading Optimization Based on Data Compression in UAV-Assisted Edge Computing
摘要
Abstract
Data compression technology can reduce the offloading energy consumption of users in mobile edge computing(MEC)by compressing computing tasks.Aiming at the problem that the communication link between the mobile users and the base station is blocked,which has an impact on communication quality,this paper proposes a task offloading scheme based on data compression to meet the requirements of emergency communication and energy-saving offloading in MEC assisted by the unmanned aerial vehicle(UAV)equipped with relay devices and edge servers.Considering constraints such as task compression ratios,system resource and the onboard energy of UAV,we formulate a problem to minimize the sum energy consumption of users.The non-convex optimization problem is modeled as a Markov decision process and the soft actor-critic algorithm based deep reinforcement learning is used to tackle the problem.The simulation results reveal that the proposed scheme achieves better convergence performance and the total energy consumption of users can be reduced by 24.7%—42.2%,compared with the benchmark algorithms.关键词
移动边缘计算/数据压缩/无人机/深度强化学习/任务卸载Key words
mobile edge computing(MEC)/data compression/unmanned aerial vehicle(UAV)/deep reinforcement learning/task offloading分类
信息技术与安全科学引用本文复制引用
李斌,朱潇,王俊义..基于数据压缩的无人机边缘计算卸载优化[J].数据采集与处理,2024,39(6):1432-1444,13.基金项目
国家自然科学基金(62101277,62371149). （62101277,62371149）
