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SAG-MEC网络下支持WPT的无人机动态任务卸载与资源分配

王怡 覃团发 韦睿 黄金宝

计算机工程2026,Vol.52Issue(5):371-382,12.
计算机工程2026,Vol.52Issue(5):371-382,12.DOI:10.19678/j.issn.1000-3428.0070030

SAG-MEC网络下支持WPT的无人机动态任务卸载与资源分配

Dynamic Task Offloading and Resource Allocation of UAVs Supported by WPT in SAG-MEC Network

王怡 1覃团发 1韦睿 1黄金宝1

作者信息

  • 1. 广西大学计算机与电子信息学院广西多媒体通信与网络技术重点实验室,广西南宁 530004
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摘要

Abstract

Remote areas face problems such as insufficient cellular network coverage as well as low energy and computing power of Internet of Things(IoT)devices.Hence,the requirements for delay-sensitive task offloading and computing for a large number of tasks cannot be met.Considering the combination of the Space-Air-Ground Integrated Network(SAGIN)and Mobile Edge Computing(MEC),this paper proposes a strategy for dynamic task offloading and resource allocation for Unmanned Aerial Vehicle(UAV)-assisted IoT devices that support Wireless Power Transmission(WPT)technology,in which UAVs are responsible for collecting compute-intensive tasks generated by IoT devices.These tasks are locally calculated or dynamically unloaded to the base station and a Low Earth Orbit(LEO)satellite for further processing using a partial unloading mode,according to the current state.Given the dynamic heterogeneous network environment,as well as the tight coupling between long-term queuing delays and short-term decision-making,this paper proposes a Twin Delayed Deep Deterministic Policy Gradient(TD3PG)algorithm based on Lyapunov optimization under queuing delay constraints.The algorithm coordinates UAVs to learn the optimal offloading strategy and resource allocation by optimizing UAV dynamic association,task allocation,computing resource allocation,and bandwidth allocation.Simulation results show that,compared with other schemes,the proposed dynamic scheme can effectively reduce the energy consumption,network backlog sum,and average queue delay in the UAV network.Under different learning rate combinations,the reward of the TD3PG algorithm increases by 13.6%and 24.0%compared with that of the Deep Deterministic Policy Gradient(DDPG)algorithm,and by 20.4%and 17.9%compared with that of the Double Deep Q-Network(DDQN)algorithm.

关键词

空天地一体化网络/移动边缘计算/无人机/任务卸载/资源分配

Key words

Space-Air-Ground Integrated Network(SAGIN)/Mobile Edge Computing(MEC)/Unmanned Aerial Vehicle(UAV)/task offloading/resource allocation

分类

信息技术与安全科学

引用本文复制引用

王怡,覃团发,韦睿,黄金宝..SAG-MEC网络下支持WPT的无人机动态任务卸载与资源分配[J].计算机工程,2026,52(5):371-382,12.

基金项目

国家自然科学基金(61563004). (61563004)

计算机工程

1000-3428

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