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Computing Power Network (CPN)

https://doi.org/10.31854/1813-324X-2025-11-5-127-144

EDN: HYREKC

Abstract

This article discusses the concept of the Computing Power Network (CPN), a new paradigm of distributed computing designed to distribute, manage and optimally use computing resources on demand by users, similar to the distribution of electrical energy in power systems.

The relevance of the study is due to the fact that with the development of the digital society, more and more applications require not only high computing power, but also low latency, which makes computing and communication networks tightly integrated. In contrast to cloud, edge and fog computing technologies, a new paradigm for organizing geographically distributed computing is required that can provide more flexible, efficient and high-quality provision of computing power on demand by users to support a variety of promising applications (artificial intelligence / machine learning, big data analysis, industrial Internet of Things, smart manufacturing, unmanned transport, etc.). By analogy with the distribution of electrical energy in power systems, a new model for distributing computing resources was recently proposed - CPN. It provides computing power as "computing energy" that can be transmitted, accumulated and consumed in a distributed network of nodes - similar to how electrical energy is distributed between generators, substations and consumers in power grids.

The aim of this study is to study the architectural and functional features of computing power networks, as well as to analyze the current state of international standardization of this technology.

Methods include analysis of scientific and regulatory literature, assessment of the state of the level of international standardization of computing power network technologies.

Results. The study analyzed the general principles of construction, structure and functional architecture of the computing power network, and determined that the full functioning of CPN requires a developed network infrastructure, primarily based on software-defined network technologies SDN and network management platforms using artificial intelligence.

Scientific novelty. The study is the first attempt to conduct a system analysis of the computing power network concept in the context of Russian-language scientific literature. The work fills the existing gap in domestic science, offering a comprehensive view of the possibilities of building and operating a network of computing power using technologies of existing and prospective communication networks.

The theoretical significance of the work lies in creating a basis for studying and integrating prospective fixed and mobile 5G / 6G communication networks with cloud and edge computing to implement the concept of a network of computing power.

About the Authors

A. V. Roslyakov
Povolzhskiy State University of Telecommunications and Informatics
Russian Federation


P. A. Aleksakhin
Povolzhskiy State University of Telecommunications and Informatics
Russian Federation


V. A. Mikhailov
Povolzhskiy State University of Telecommunications and Informatics
Russian Federation


References

1. Rec. ITU-T Y.2501. Computing Power Network – framework and architecture. 2021.

2. Smelyansky R.L. Evolution of the computing infrastructure. Bulletin of Moscow University. Series 15. Computational Mathematics and Cybernetics. 2024;4:190–233. (in Russ.) DOI:10.55959/MSU/01370782152024474190234. EDN:OZHXTV

3. Foster I., Zhao Y., Raicu I., Lu S. Cloud Computing and Grid Computing 360-Degrees Compared. Proceedings of the Grid Computing Environment Workshop, 12–16 November 2008, Austin, USA. IEEE; 2008. DOI:10.1109/GCE.2008.4738445

4. Duan Q. Service-Oriented Network Virtualization for Composition of Cloud Computing and Networking. International Journal of Next-Generation Computing. 2011;2(2):123–138.

5. Huawei Technology Report. Computing 2030. 2023. https://www-file.huawei.com/-/media/corp2020/pdf/giv/intelligent_world_2030_en.pdf

6. Lei B., Liu Z., Wang X., Yang M., Chen Y. Computing network: A new multiaccess edge computing. Telecommunications Science. 2019;35(9):44–51.

7. Yukun S., Bo L., Junlin L., Haonan H., Xing Z., Jing P. Computing power network: A survey. China Communications. 2024; 21(9):109–145. DOI:10.23919/JCC.ja.2021-0776

8. Zhao Q., Lei B., Wei M. Survey of computing power network. ITU Journal on Future and Evolving Technologies. 2022;3(3): 632–644. DOI:10.52953/BXBJ6384. EDN:WJMMIH

9. Jia Q., Hu Y., Zhou X., Ma Q., Guo K., Zhang H., Xie R., Huang T., Liu Y. Deterministic Computing Power Networking: Architecture, Technologies and Prospects. arXiv:2401.17812. 2024. DOI:10.48550/arXiv.2401.17812

10. Lei B., Zhao Q., Mei J. Computing Power Network: An Interworking Architecture of Computing and Network Based on IP Extension. Proceedings of the 22nd International Conference on High Performance Switching and Routing, HPSR, 07–10 June 2021, Paris, France. IEEE; 2021. DOI:10.1109/HPSR52026.2021.9481792

11. Li S., Li T., Zhou X. Computing Power Network: A Network-Centric Supply Paradigm for Integrated Resources. ZTE Technology Journal. 2021;27(3):29–34. DOI:10.12142/ZTETJ.202103007

12. Tang X., Cao C., Wang Y., Zhang S., Liu Y., Li M., et al. Computing power network: The architecture of convergence of computing and networking towards 6G requirement. China Communications. 2021;18(2):175–185. DOI:10.23919/JCC.2021.02.01.1. EDN:FDUIVB

13. Cao C., Zhang S., Liu Y., Tang X. Convergence of telco cloud and bearer network based computing power network orchestration. Telecommunications Science. 2020;36(7):55–62.

14. Lei B., Wang J., Zhao Q., Yu Y., Yang M. Novel network virtualization architecture based on the convergence of computing, storage and transport resources. Telecommunications Science. 2020;36(7):42–54.

15. Liu J., Sun Y., Su J., Li Z., Zhang X., Lei B., et al. Computing Power Network: A Testbed and Applications with Edge Intelligence. Proceedings of the Conference on Computer Communications Workshops, INFOCOM WKSHPS, 02–05 May 2022, New York, USA. IEEE; 2022. DOI:10.1109/INFOCOMWKSHPS54753.2022.9798112

16. Smeliansky R. Network powered by computing: Next generation of computational infrastructure. Edge Computing – Technology, Management and Integration. IntechOpen. 2023. p.47‒70. DOI:10.5772/intechopen.110178

17. Smeliansky R. Network Powered by Computing. Proceedings of the International Conference on Modern Network Technologies, MoNeTec, 27–29 October 2022, Moscow, Russian Federation. IEEE; 2022. DOI:10.1109/MoNeTec55448.2022.9960771

18. Glushak E.V. Cloud and fog computing: architecture, modeling, application. Moscow, Vologda: Infra-Engineering Publ.; 2025. 180 p. (in Rus.) EDN:BUZGWB

19. Roslyakov A.V., Vanyashin S.V., Grebeshkov A.Yu., Samsonov M.Yu. Internet of Things. Samara: PSUTI Publ.; 2014. 342 p. (in Rus.)

20. Roslyakov A.V., Gerasimov V.V. Deterministic networks and their standardization. Standards and Quality. 2024;7:42–47. (in Rus.) DOI:10.35400/0038-9692-2024-7-70-24. EDN:UTBDXB

21. Efimenko A.A., Fedoseev S.V. Organization of cloud computing infrastructure based on SDN network. Statistics and Economics. 2013;5:185–187. (in Rus.) EDN:RPFQDD

22. Roslyakov A.V., Gerasimov V.V., Mamoshina Yu.S., Sudareva M.E. Standardization of time-synchronized TSN networks. Standards and Quality. 2021;4:48–53. (in Rus.) DOI:10.35400/0038-9692-2021-4-48-53

23. Rec. ITU-T Q.4140. Protocols and signalling for computing power networks. Signalling requirements for service deployment in computing power networks. 2023.

24. Rec. ITU-T Q.4141. Protocols and signalling for computing power networks. Requirements and signalling of intelligence control for the border network gateway in computing power networks. 2023.


Review

For citations:


Roslyakov A.V., Aleksakhin P.A., Mikhailov V.A. Computing Power Network (CPN). Proceedings of Telecommunication Universities. 2025;11(5):127-144. (In Russ.) https://doi.org/10.31854/1813-324X-2025-11-5-127-144. EDN: HYREKC

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ISSN 1813-324X (Print)
ISSN 2712-8830 (Online)