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

SONG Zheng-Yu; HAO Yuan-Yuan; SUN Xin

doi:10.12263/DZXB.20201249

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

PAPERS | 更新时间：2025-12-11

- Computation Offloading and Resource Allocation Algorithm for Collaborative LEO Satellite Multi-Access Edge Computing
- ACTA ELECTRONICA SINICA Vol. 50, Issue 3, Pages: 567-573(2022)
- 作者机构：
  
  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
- 作者简介：
- 基金信息：
- DOI：10.12263/DZXB.20201249
  CLC： TN927
- Received：06 November 2020，
  
  Revised：2021-08-03，
  
  Published：25 March 2022
- 稿件说明：
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宋政育,郝媛媛,孙昕.低轨卫星协作边缘计算任务迁移和资源分配算法[J].电子学报,2022,50(03):567-573.

SONG Zheng-Yu,HAO Yuan-Yuan,SUN Xin.Computation Offloading and Resource Allocation Algorithm for Collaborative LEO Satellite Multi-Access Edge Computing[J].ACTA ELECTRONICA SINICA,2022,50(03):567-573.
宋政育,郝媛媛,孙昕.低轨卫星协作边缘计算任务迁移和资源分配算法[J].电子学报,2022,50(03):567-573. DOI： 10.12263/DZXB.20201249.

SONG Zheng-Yu,HAO Yuan-Yuan,SUN Xin.Computation Offloading and Resource Allocation Algorithm for Collaborative LEO Satellite Multi-Access Edge Computing[J].ACTA ELECTRONICA SINICA,2022,50(03):567-573. DOI： 10.12263/DZXB.20201249.

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.

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.

关键词

Keywords

references

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