电子学报 ›› 2022, Vol. 50 ›› Issue (3): 567-573.DOI: 10.12263/DZXB.20201249

• 学术论文 • 上一篇    下一篇

低轨卫星协作边缘计算任务迁移和资源分配算法

宋政育1, 郝媛媛2,3, 孙昕1   

  1. 1.北京交通大学电子信息工程学院, 北京 100044
    2.中国空间技术研究院通信与导航卫星总体部, 北京 100094
    3.国家航天局卫星通信系统创新中心, 北京 100094
  • 收稿日期:2020-11-06 修回日期:2021-08-03 出版日期:2022-03-25 发布日期:2022-03-25
  • 作者简介:宋政育 男,1984年生于山东威海.现为北京交通大学电子信息工程学院副教授、硕士生导师.主要研究方向为空天地一体化通信,移动边缘计算,智能超表面通信,物联网以及专业移动通信等.E-mail:songzy@bjtu.edu.cn
    郝媛媛(通讯作者) 女,1995年生于河北廊坊.现为中国空间技术研究院通信与导航卫星总体部工程师.主要研究方向为与5G/6G融合的卫星互联网络通信系统,无人机通信,物联网以及移动边缘计算等.E-mail:tracyhao@bit.edu.cn
    孙 昕 女,1967年生于吉林通化.现为北京交通大学电子信息工程学院教授、博士生导师.主要研究方向为专业移动通信系统,卫星通信以及物联网等.E-mail:xsun@bjtu.edu.cn
  • 基金资助:
    国家自然科学基金青年基金(61901027)

Computation Offloading and Resource Allocation Algorithm for Collaborative LEO Satellite Multi-Access Edge Computing

SONG Zheng-Yu1, HAO Yuan-Yuan2,3, SUN Xin1   

  1. 1.School of Electronic and Information Engineering,Beijing Jiaotong University,Beijing 100044,China
    2.Institute of Telecommunication and Navigation Satellites,China Academy of Space Technology,Beijing 100094,China
    3.Innovation Center of Satellite Communication System,China National Space Administration,Beijing 100094,China
  • Received:2020-11-06 Revised:2021-08-03 Online:2022-03-25 Published:2022-03-25

摘要:

研究了基于星间链路的低轨卫星协作边缘计算任务迁移和资源分配问题,为偏远地区用户提供边缘计算服务.采用部分任务迁移机制,以地面用户加权总能耗最小化为目标建立优化问题,提出了一种低轨卫星协作边缘计算的任务迁移和资源分配算法,基于优化问题的非凸性,将其分解为任务迁移子问题和资源分配子问题,分别采用标准凸优化方法和拉格朗日对偶分解方法进行求解.仿真结果表明,该算法的收敛速度快;与本地计算和任务数据全部上传算法相比,本文所提出的算法可至少降低约74%的用户总能耗;与非协作卫星边缘计算相比,基于星间链路的低轨卫星协作边缘计算可至少降低约22%的用户总能耗,且星间链路的信道容量越大,用户总能耗越低.

关键词: 卫星通信, 协作边缘计算, 星间链路, 任务迁移, 资源分配, 加权总能耗

Abstract:

In order to provide edge computing services for users in remote regions, the computation offloading and resource allocation problem for collaborative low-earth orbit (LEO) satellite multi-access edge computing (MEC) with the aid of inter-satellite link (ISL) is investigated. By applying the partial offloading scheme, the optimization problem is formulated to minimize the weighted sum energy consumption of ground users, and a computation offloading and resource allocation algorithm for LEO satellite collaborative MEC is proposed. Due to the non-convexity of the formulated problem, it is decoupled into computation offloading and resource allocation subproblems, and then solved by standard convex optimization and Lagrangian dual decomposition method, respectively. Simulation results show that the proposed algorithm converges fast. Compared with local computing and full offloading algorithms, the proposed algorithm can reduce the energy consumption of users by 74% at least. Additionally, compared with non-collaborative satellite MEC, LEO satellite collaborative MEC based on the ISL can reduce the energy consumption of users by 22% at least. By increasing the capacity of ISL, the energy consumption of users is continuously decreased.

Key words: satellite communications, collaborative edge computing, inter-satellite link, computation offloading, resource allocation, weighted sum energy consumption

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