首页|恶意干扰下的无人机辅助边缘计算加权能耗与时延智能优化

恶意干扰下的无人机辅助边缘计算加权能耗与时延智能优化

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近年来,将移动边缘计算(MEC)服务器搭载在无人机(UAV)上为地面移动用户提供服务备受学术界和工业界广泛的关注.但在恶意干扰环境下,如何有效调度资源降低系统时延和能耗成为关键问题.为此,针对干扰机影响下无人机辅助边缘计算的问题,该文建立一个以最小化加权能耗与时延为目标的模型,联合优化无人机飞行轨迹、资源调度和任务分配来提升无人机辅助移动边缘计算系统性能.鉴于优化问题难求解以及恶意干扰行为动态多变,该文提出了一种基于双延迟深度确定性策略梯度(TD3)的资源调度算法,同时结合优先经验回放(PER)机制提高算法收敛速度和稳定性,高效对抗恶意干扰攻击.仿真结果表明所提算法较其他算法,能够有效降低系统的时延和能耗,并具有很好的收敛性与稳定性.
Intelligent Weighted Energy Consumption and Delay Optimization for UAV-Assisted MEC Under Malicious Jamming
In recent years,mounting Mobile Edge Computing(MEC)servers on Unmanned Aerial Vehicle(UAV)to provide services for mobile ground users has been widely researched in academia and industry.However,in malicious jamming environments,how to effectively schedule resources to reduce system delay and energy consumption becomes a key challenge.Therefore,this paper considers a UAV-assisted MEC system under a malicious jammer,where an optimization model is established to minimize the weighted energy consumption and delay by jointly optimizing UAV flight trajectories,resource scheduling,and task allocation.As the optimization problem is difficult to be solved and the malicious jamming behavior is dynamic,a Twin Delayed Deep Deterministic(TD3)policy gradient algorithm is proposed to search for the optimal policy.At the same time,the Prioritized Experience Replay(PER)technique is added to improve the convergence speed and stability of the algorithm,which is highly effective against malicious interference attacks.The simulation results show that the proposed algorithm can effectively reduce the delay and energy consumption,and achieve good convergence and stability compared with other algorithms.

Unmanned Aerial Vehicle(UAV)communicationMobile Edge Computing(MEC)Resource schedulingAnti-jammingDeep Reinforcement Learning(DRL)

杨和林、郑梦婷、刘帅、肖亮、谢显中、熊泽辉

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厦门大学信息学院 厦门 361005

重庆邮电大学重庆市计算机网络与通信技术重点实验室 重庆 400065

新加坡科技设计大学信息系统技术与设计学院 新加坡 487372

无人机通信 移动边缘计算 资源调度 抗干扰 深度强化学习

国家自然科学基金国家自然科学基金国家自然科学基金国家自然科学基金中央高校基本科研业务费专项厦门市自然科学基金项目科技部重点研发计划"小米青年学者"项目

6237140862301467U21A2044461971366207202200803502Z2023710102023YFB3107603

2024

电子与信息学报
中国科学院电子学研究所 国家自然科学基金委员会信息科学部

电子与信息学报

CSTPCD北大核心
影响因子:1.302
ISSN:1009-5896
年,卷(期):2024.46(7)
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