LEO Satellite Assisted Edge Computing With Latency and Energy Optimization

IF 6.7 2区计算机科学 Q1 ENGINEERING, MULTIDISCIPLINARY

IEEE Transactions on Network Science and Engineering Pub Date : 2025-03-14 DOI:10.1109/TNSE.2025.3551273

Ao Li;Ting Zhou;Tianheng Xu;Yuling Ouyang;Honglin Hu;Celimuge Wu

{"title":"LEO Satellite Assisted Edge Computing With Latency and Energy Optimization","authors":"Ao Li;Ting Zhou;Tianheng Xu;Yuling Ouyang;Honglin Hu;Celimuge Wu","doi":"10.1109/TNSE.2025.3551273","DOIUrl":null,"url":null,"abstract":"Low earth orbit (LEO) satellite networks hold significant promise for delivering global communication services in next-generation mobile communication networks. The integration of edge computing with LEO satellite networks enables stable and reliable communication and computation services for ground user equipment (UE). This paper proposes an LEO satellite-assisted cooperative edge computing framework, where UEs and the LEO satellite collaboratively process divisible computational tasks. A system cost function is proposed to quantify both latency and energy consumption during task execution. Building on this, we formulate an optimization problem to minimize the system cost function by optimizing offloading decisions, power control, task scheduling, local computational capacity, and LEO satellite computing resource allocation. To solve this problem, we propose a discrete whale optimization algorithm with a nonlinear convergence factor and adaptive weight (NAWOA), characterized by low computational complexity. The superiority and validity of the proposed algorithm are demonstrated via numerical simulations that compare different algorithms and computational offloading schemes.","PeriodicalId":54229,"journal":{"name":"IEEE Transactions on Network Science and Engineering","volume":"12 4","pages":"2640-2653"},"PeriodicalIF":6.7000,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Network Science and Engineering","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10925906/","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}

引用次数: 0

Abstract

Low earth orbit (LEO) satellite networks hold significant promise for delivering global communication services in next-generation mobile communication networks. The integration of edge computing with LEO satellite networks enables stable and reliable communication and computation services for ground user equipment (UE). This paper proposes an LEO satellite-assisted cooperative edge computing framework, where UEs and the LEO satellite collaboratively process divisible computational tasks. A system cost function is proposed to quantify both latency and energy consumption during task execution. Building on this, we formulate an optimization problem to minimize the system cost function by optimizing offloading decisions, power control, task scheduling, local computational capacity, and LEO satellite computing resource allocation. To solve this problem, we propose a discrete whale optimization algorithm with a nonlinear convergence factor and adaptive weight (NAWOA), characterized by low computational complexity. The superiority and validity of the proposed algorithm are demonstrated via numerical simulations that compare different algorithms and computational offloading schemes.

查看原文本刊更多论文

低轨道卫星辅助边缘计算的时延和能量优化

低地球轨道（LEO）卫星网络在下一代移动通信网络中提供全球通信服务具有重要的前景。边缘计算与低轨道卫星网络的集成为地面用户设备（UE）提供稳定可靠的通信和计算服务。本文提出了一种低轨道卫星辅助下的协同边缘计算框架，在该框架下，ue与低轨道卫星协同处理可分割的计算任务。提出了一个系统成本函数来量化任务执行过程中的延迟和能耗。在此基础上，通过优化卸载决策、功率控制、任务调度、局部计算能力和LEO卫星计算资源分配，提出了最小化系统成本函数的优化问题。为了解决这一问题，我们提出了一种具有非线性收敛因子和自适应权值（NAWOA）的离散鲸鱼优化算法，该算法具有计算复杂度低的特点。通过数值仿真比较了不同算法和计算卸载方案，验证了该算法的优越性和有效性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

IEEE Transactions on Network Science and Engineering Engineering-Control and Systems Engineering

CiteScore

12.60

自引率

9.10%

发文量

393

期刊介绍： The proposed journal, called the IEEE Transactions on Network Science and Engineering (TNSE), is committed to timely publishing of peer-reviewed technical articles that deal with the theory and applications of network science and the interconnections among the elements in a system that form a network. In particular, the IEEE Transactions on Network Science and Engineering publishes articles on understanding, prediction, and control of structures and behaviors of networks at the fundamental level. The types of networks covered include physical or engineered networks, information networks, biological networks, semantic networks, economic networks, social networks, and ecological networks. Aimed at discovering common principles that govern network structures, network functionalities and behaviors of networks, the journal seeks articles on understanding, prediction, and control of structures and behaviors of networks. Another trans-disciplinary focus of the IEEE Transactions on Network Science and Engineering is the interactions between and co-evolution of different genres of networks.