计算机工程2025，Vol.51Issue(5)：43-51,9.DOI:10.19678/j.issn.1000-3428.0069181
基于MEC的空天地一体化网络任务分割与资源分配
Task Segmentation and Resource Allocation in MEC-Based Space-Air-Ground Integrated Networks
摘要
Abstract
In the 6G era,a Space-Air-Ground Integrated Network(SAGIN)can provide ubiquitous coverage for Internet of Things(IoT)devices and can therefore effectively address the current inadequacies in network architecture coverage capabilities.Multi-access Edge Computing(MEC)is a crucial technology that further enhances the service capabilities of SAGIN,demonstrating significant abilities in reducing task execution latency and system energy consumption.This paper proposes an MEC-based SAGIN architecture in which satellites and multiple Unmanned Aerial Vehicles(UAVs)act as edge nodes that offers computational power in close proximity to IoT devices.Through the task segmentation of IoT devices and bandwidth allocation for UAVs and satellites,the proposed architecture intends to minimize the average network energy consumption.The problem of high network dynamics is reformulated as a Markov Decision Process(MDP),and a low-complexity adaptive decision algorithm based on Deep Deterministic Policy Gradient(DDPG)is introduced as its solution.Simulation results demonstrate that the algorithm performs well in minimizing network energy consumption and maximizing the cumulative rewards for the DDPG Agent.关键词
深度确定性策略梯度算法/空天地一体化网络/边缘计算/资源分配/任务分割Key words
Deep Deterministic Policy Gradient(DDPG)algorithm/Space-Air-Ground Integrated Network(SAGIN)/edge computing/resource allocation/task segmentation分类
信息技术与安全科学引用本文复制引用
杜剑波,董伟哲,金蓉,王军选,康嘉文,刘雷,策力木格..基于MEC的空天地一体化网络任务分割与资源分配[J].计算机工程,2025,51(5):43-51,9.基金项目
国家自然科学基金(62271391) （62271391）
陕西省教育厅服务地方专项科研项目(21JC032). （21JC032）
