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- Tao Chen College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, China
College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, China
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- Yi Zhuang College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, China
College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, China
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SPCNC '23: Proceedings of the 2nd International Conference on Signal Processing, Computer Networks and CommunicationsDecember 2023Pages 390–396https://doi.org/10.1145/3654446.3654516
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SPCNC '23: Proceedings of the 2nd International Conference on Signal Processing, Computer Networks and Communications
A Dynamic Hierarchical Single Link Fault Recovery Scheme for SDN Based on Dynamic Hierarchies
Pages 390–396
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ABSTRACT
In the currently commonly used proactive recovery mechanisms for network failures, the pre-set backup paths are usually not dynamically updated and may suffer from traffic congestion problems after recovery. In this paper, a single-link failure recovery model based on dynamic hierarchy for SDN is proposed for the traffic congestion problem that may occur after the recovery of link failures in low-rail interconnection networks. Based on the change rule of link traffic, the Transformer model is used to predict the future available traffic on the link, and the link is dynamically evaluated to quickly realize adaptive fault recovery. The proposed scheme has the advantages of low overhead and high speed. Through comparative experiments, the effectiveness of the scheme proposed in this paper is verified, and compared with similar schemes can achieve a lower maximum bandwidth utilization rate, and more effectively prevent possible congestion problems after fault recovery.
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Index Terms
A Dynamic Hierarchical Single Link Fault Recovery Scheme for SDN Based on Dynamic Hierarchies
Networks
Network properties
Network reliability
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SPCNC '23: Proceedings of the 2nd International Conference on Signal Processing, Computer Networks and Communications
December 2023
435 pages
ISBN:9798400716430
DOI:10.1145/3654446
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- Published: 3 May 2024
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