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A Knowledge-driven Self-healing Dual-loop and Validation for Autonomous Networks

Published: 03 August 2024 Publication History

Abstract

Intelligent technology is driving the communication industry to a higher stage of autonomy. To enable the large-scale deployment of Autonomous Networks (ANs), We design a knowledge-driven self-healing dual-loop architecture throughout the fault lifecycle, Then we propose an optimization model that aims to minimize the loss of services operation. Simulations are conducted in a programmable network to validate the loop.

References

[1]
[1] Aaron Boasman-Patel and Dong Sun. Autonomous networks: Empowering digital transformation-evolving from level 2/3 towards level 4. Technical report, TM Forum, 2 2023.
[2]
[2] Peng Yu et al. Digital twin driven service self-healing with graph neural networks in 6g edge networks. IEEE Journal on Selected Areas in Communications, 41(11):3607–3623, 2023.
[3]
[3] Yinlin Ren et al. End-to-end network sla quality assurance for c-ran: A closed-loop management method based on digital twin network. IEEE Transactions on Mobile Computing, 23(5):4405–4422, 2024.
[4]
[4] Honglin Fang, Di Zhang, Can Tan, et al. Large language model enhanced autonomous agents for proactive fault-tolerant edge networks. In IEEE INFOCOM 2024 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), pages 1–2, 2024.

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APNet '24: Proceedings of the 8th Asia-Pacific Workshop on Networking
August 2024
230 pages
ISBN:9798400717581
DOI:10.1145/3663408
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 03 August 2024

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Author Tags

  1. Autonomous Networks
  2. Network fault management
  3. Self-healing

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  • Poster
  • Research
  • Refereed limited

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APNet 2024

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APNet '24 Paper Acceptance Rate 50 of 118 submissions, 42%;
Overall Acceptance Rate 50 of 118 submissions, 42%

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