空天地海一体化算力资源管理技术研究及展望

田厉锋; 张佳宇; 李昕; 曾德泽; 姜楠

doi:10.11959/j.issn.1000-0801.2025012

您当前的位置：

首页 >

文章列表页 >

空天地海一体化算力资源管理技术研究及展望

研究 | 更新时间：2025-07-04

- 空天地海一体化算力资源管理技术研究及展望
- Research and Prospect of Integrated Computing Resource Management Technologies for Space-Air-Ground-Sea Networks
- 天地一体化信息网络 2025年6卷第2期页码：1-10
- 作者机构：
  
  1.中国地质大学（武汉），湖北武汉 430074
  2.华东交通大学，江西南昌 330013
- 作者简介：
  
  [ "田厉锋（1993- ），男，中国地质大学（武汉）计算机学院博士生，主要从事分布式计算研究工作。" ]
  张佳宇（2000- ），男，中国地质大学（武汉）未来技术学院硕士生，主要研究方向为低地球轨道卫星边缘计算。
  李昕（1998- ），男，中国地质大学（武汉）未来技术学院硕士生，主要研究方向为卫星边缘计算。
  曾德泽（1984- ），男，中国地质大学（武汉）计算机学院教授，主要从事边缘计算、云计算等领域的研究工作。
  姜楠（1981- ），男，华东交通大学信息与软件工程学院教授，主要从事人工智能、物联网等领域的研究工作。
- 基金信息：
  
  国家自然科学基金资助项目(62432015;62172375);湖北省重点研发计划(2023BAB065);中国地质大学（武汉）“地大学者”科学研究基金(2022179)
- DOI：10.11959/j.issn.1000-0801.2025012
  中图分类号： TP393
- 收稿：2024-12-30，
  
  修回：2025-04-30，
  
  纸质出版：2025-06-20
- 稿件说明：
移动端阅览
田厉锋,张佳宇,李昕等.空天地海一体化算力资源管理技术研究及展望[J].天地一体化信息网络,2025,06(02):1-10.

TIAN Lifeng,ZHANG Jiayu,LI Xin,et al.Research and Prospect of Integrated Computing Resource Management Technologies for Space-Air-Ground-Sea Networks[J].Space-Integrated-Ground Information Networks,2025,06(02):1-10.
田厉锋,张佳宇,李昕等.空天地海一体化算力资源管理技术研究及展望[J].天地一体化信息网络,2025,06(02):1-10. DOI： 10.11959/j.issn.1000-0801.2025012.

TIAN Lifeng,ZHANG Jiayu,LI Xin,et al.Research and Prospect of Integrated Computing Resource Management Technologies for Space-Air-Ground-Sea Networks[J].Space-Integrated-Ground Information Networks,2025,06(02):1-10. DOI： 10.11959/j.issn.1000-0801.2025012.

摘要

跨区域、碎片化边端算力的整合与编排是推进算力基础设施高质量发展的关键环节。空、天、地、海等多样化的工作环境，共同构成了一个复杂的异构算力资源网络。面对海量且多样的算力资源，不同算力平台在硬件性能、资源分布及环境适应性方面存在显著差异，传统的算力管理方式已难以满足高效、动态的资源调度需求。因此，亟须建立一个“大一统”的管理框架，以实现高效的感知、整合与编排调度。提出串联空天地海边端设备、打通区域算力壁垒的一体化算力资源管理架构。基于算力网技术的发展现状，分析部署于太空、天空、海洋和陆地的边端设备的资源优势及环境特征，构建纳管多区域边端算力设备，包含多个逻辑结构的一体化算力资源管理架构。总结在算力资源管理架构构建过程中面临的资源感知与纳管、算力拓扑更新以及算力编排调度等挑战，并提出相应的关键技术路径和研究展望。为边端算力基础设施的建设提供坚实的理论支持，助力实现多环境下高效、动态的算力资源管理与优化。

Abstract

The integration of cross-regional

fragmented edge computing resources is a key aspect in advancing the high-quality development of edge computing infrastructure. Diverse operational environments—encompassing space

air

ground

and sea—jointly form a large-scale network of computing resources. Given the vast scale and diversity of these resources

significant disparities exist across computing platforms in terms of hardware performance

resource distribution and environmental adaptability. Traditional management methods are increasingly inadequate to meet the demands of efficient and dynamic scheduling. Therefore

there is an urgent need to establish a unified management framework capable of enabling efficient sensing

integration

and orchestration of computing resources. We proposes an integrated resource management architecture to interconnect edge devices across space

air

ground and sea to break down regional computing barriers. Based on the current network technologies

we analyzes the resource advantages and environmental characteristics of edge devices deployed in these varied domains. An integrated architecture comprising multiple logical layers is constructed to manage edge computing resources across regions. This paper summarizes key challenges encountered in the development of such an architecture

including resource sensing and registration

computing topology updates

and resource orchestration and scheduling. It further outlines critical research directions

providing robust theoretical support for the construction of infrastructure and optimization of computing resources across heterogeneous environments.

关键词

Keywords

references

刘畅 . 中共中央关于制定国民经济和社会发展第十四个五年规划和二〇三五年远景目标的建议［EB］. 2024 .

LIU C . Proposal of the central committee of the communist party of China on formulating the 14th five-year plan for national economic and social development and the long-range objectives through the year 2035 [EB ] . 2024 .

中国信息通信研究院 . 科研能力权威发布白皮书［EB］. 2024 .

China Academy of Information and Communications Technology . White paper on authoritative assessment of research capability [EB ] . 2024 .

吴卓然 . 什么是算力网络？为什么需要算力和算力网络？［EB］. 2022 .

WU Z R . What is a computing power network? Why do we need computing power and computing power networks?［EB］. 2022 .

ZHANG Q , CHENG L , BOUTABA R . Cloud computing: state-of-the-art and research challenges [J ] . Journal of Internet Services and Applications , 2010 , 1 ( 1 ): 7 - 18 .

SHI W S , CAO J , ZHANG Q , et al . Edge computing: vision and challenges [J ] . IEEE Internet of Things Journal , 2016 , 3 ( 5 ): 637 - 646 .

KRATZKE N , QUINT P C . Understanding cloud-native applications after 10 years of cloud computing - A systematic mapping study [J ] . Journal of Systems and Software , 2017 , 126 : 1 - 16 .

WANG J J , FENG Z Q , GEORGE S , et al . Towards scalable edge-native applications [C ] // Proceedings of the 4th ACM/IEEE Symposium on Edge Computing . New York : ACM , 2019 : 152 - 165 .

中国移动研究院 . 面向智算的算力原生白皮书［EB］. 2024 .

China Mobile CMRI . Native white paper on computing power for intelligent computing ［EB］. 2024 .

ZHU B T , LIN S Y , ZHU Y F , et al . Collaborative hyperspectral image processing using satellite edge computing [J ] . IEEE Transactions on Mobile Computing , 2024 , 23 ( 3 ): 2241 - 2253 .

OUYANG Q L , YE N , GAO J , et al . Joint in-orbit computation and communication for minimizing download time from LEO satellites [J ] . IEEE Transactions on Mobile Computing , 2024 , 23 ( 5 ): 3950 - 3963 .

ZHANG X Y , LIU J , ZHANG R , et al . Energy-efficient computation peer offloading in satellite edge computing networks [J ] . IEEE Transactions on Mobile Computing , 2024 , 23 ( 4 ): 3077 - 3091 .

BAI Z Y , LIN Y F , CAO Y , et al . Delay-aware cooperative task offloading for multi-UAV enabled edge-cloud computing [J ] . IEEE Transactions on Mobile Computing , 2024 , 23 ( 2 ): 1034 - 1049 .

DAI X X , XIAO Z , JIANG H B , et al . UAV-assisted task offloading in vehicular edge computing networks [J ] . IEEE Transactions on Mobile Computing , 2024 , 23 ( 4 ): 2520 - 2534 .

WANG Y M , FENG W , WANG J , et al . Hybrid satellite-UAV-terrestrial networks for 6G ubiquitous coverage: a maritime communications perspective [J ] . IEEE Journal on Selected Areas in Communications , 2021 , 39 ( 11 ): 3475 - 3490 .

YANG T T , CUI Z Q , ALSHEHRI A H , et al . Distributed maritime transport communication system with reliability and safety based on blockchain and edge computing [J ] . IEEE Transactions on Intelligent Transportation Systems , 2022 : 1 - 11 .

XIAO Y , KRUNZ M . AdaptiveFog: a modelling and optimization framework for fog computing in intelligent transportation systems [J ] . IEEE Transactions on Mobile Computing , 2022 , 21 ( 12 ): 4187 - 4200 .

段晓东 , 姚惠娟 , 付月霞 , 等 . 面向算网一体化演进的算力网络技术 [J ] . 电信科学 , 2021 , 37 ( 10 ): 76 - 85 .

DUAN X D , YAO H J , FU Y X , et al . Computing force network technologies for computing and network integration evolution [J ] . Telecommunications Science , 2021 , 37 ( 10 ): 76 - 85 .

张宏科 , 于成晓 , 权伟 , 等 . 融算网络体系基础研究［J］. 电子学报 , 2022 , 50 ( 12 ): 2928 - 2934 .

ZHANG H K , YU C X , QUAN W , et al . Fundamental research on computing integration networking [J ] . Acta Electronica Sinica , 2022 , 50 ( 12 ): 2928 - 2934 .

刘泽宁 , 李凯 , 吴连涛 , 等 . 多层次算力网络中代价感知任务调度算法［J］. 计算机研究与发展 , 2020 , 57 （ 9 ）: 1810 - 1822 .

LIU Z N , LI K , WU L T , et al . CATS: cost aware task scheduling in multi-tier computing networks [J ] . Journal of Computer Research and Development , 2020 , 57 ( 9 ): 1810 - 1822 .

柴若楠 , 郜帅 , 兰江雨 , 等 . 算力网络中高效算力资源度量方法 [J ] . 计算机研究与发展 , 2023 , 60 ( 4 ): 763 - 771 .

CHAI R N , GAO S , LAN J Y , et al . Efficient computing resource metric method in computing-first network [J ] . Journal of Computer Research and Development , 2023 , 60 ( 4 ): 763 - 771 .

KAUSHIK P , RAO A M , SINGH D P , et al . Cloud computing and comparison based on service and performance between Amazon AWS, microsoft azure, and google cloud [C ] // Proceedings of the 2021 International Conference on Technological Advancements and Innovations (ICTAI) . Piscataway : IEEE Press , 2021 : 268 - 273 .

WANG C , ZHANG Y R , LI Q , et al . Satellite computing: a case study of cloud-native satellites [C ] // Proceedings of the 2023 IEEE International Conference on Edge Computing and Communications (EDGE) . Piscataway : IEEE Press , 2023 : 262 - 270 .

LI Y J , LI H W , LIU W , et al . A case for stateless mobile core network functions in space [C ] // Proceedings of the ACM SIGCOMM 2022 Conference . New York : ACM , 2022 : 298 - 313 .

CHENG L , FENG G , SUN Y , et al . Dynamic computation offloading in satellite edge computing [C ] // Proceedings of the ICC 2022 - IEEE International Conference on Communications . Piscataway : IEEE Press , 2022 : 4721 - 4726 .

WU C , LI Y , XU M , et al . A comprehensive survey on orbital edge computing: systems, applications, and algorithms ［Z］. arXiv, 2023 .

SERRANO P , GRAMAGLIA M , MANCINI F , et al . Balloons in the sky: unveiling the characteristics and trade-offs of the google loon service [J ] . IEEE Transactions on Mobile Computing , 2023 , 22 ( 6 ): 3165 - 3178 .

LU D , XIONG C K , LYU B Z , et al . Multi-mode hybrid aerial underwater vehicle with extended endurance [C ] // Proceedings of the 2018 OCEANS - MTS/IEEE Kobe Techno-Oceans (OTO) . Piscataway : IEEE Press , 2018 : 1 - 7 .

ORNABENE R ， HOFFMAN M ， ASTLER D , et al . Design status of Gondola for high-altitude planetary science： E-20154 [Z ] . 2023 .

Current status of a NASA high-altitude balloon-based observatory for planetary science | AIAA AVIATION Forum [Z ] . 2015 .

DURAIBABU D B , LEEN G , TOAL D , et al . Underwater depth and temperature sensing based on fiber optic technology for marine and fresh water applications [J ] . Sensors , 2017 , 17 ( 6 ): 1228 .

Networking in oceans: a survey [J ] . ACM Computing Surveys , 2021 : 541 .

SCHMIDT D , WILCOCK W , LEVEQUE R , et al . Earthquake and tsunami early warning on the Cascadia subduction zone： a feasibility study for an offshore geophysical monitoring network [J ] . Geology , Engineering, Environmental Science, 2019 .

浏览量

240

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

暂无数据