Efficient Multi-Topology Failure Tolerance Mechanism in Polymorphic Network

Enhancing the failure tolerance ability of networks is crucial, as node or link failures are common occurrences on-site. The current fault tolerance schemes are divided into reactive and proactive schemes. The reactive scheme requires detection and repair after the failure occurs, which may lead to long-term network interruptions. The proactive scheme can reduce recovery time through preset backup paths, but requires additional resources. Aiming at the problems of long recovery time or high overhead of the current failure tolerance schemes, the Polymorphic Network adopts field-definable network baseline technology, which can support diversified addressing and routing capabilities, making it possible to implement a more complex and efficient failure tolerance scheme. Inspired by this, we propose an efficient Multi-topology Failure Tolerance mechanism in Polymorphic Network (MFT-PN). The MFT-PN embeds a failure recovery function into the packet processing logic by leveraging the full programmable characteristics of the network element, improving failure recovery efficiency. The backup path information is pushed into the header of the failed packet to reduce the flow table storage overhead. Meanwhile, MFT-PN introduces the concept of multi-topology routing by constructing multiple logical topologies, with each topology adopting different failure recovery strategies. Then, we design a multi-topology loop-free link backup algorithm to calculate the backup path for each topology, providing extensive coverage for different failure scenarios. Experimental results show that compared with the existing strategies, MFT-PN can reduce resource overhead by over 72% and the packet loss rate by over 59%, as well as effectively cope with multiple failure scenarios.

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Publication Details

Journal
Electronics
Published
2025-09-09
DOI
https://doi.org/10.3390/electronics14183573
Primary Topic
Software-Defined Networks and 5G
Type
article
Field-Weighted Citation Impact
0.00

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article

Efficient Multi-Topology Failure Tolerance Mechanism in Polymorphic Network

Ziyong Li, Le Tian, Wenyu Jiang, Bai Lin
Electronics
Software-Defined Networks and 5G
article

Efficient Multi-Topology Failure Tolerance Mechanism in Polymorphic Network

Ziyong Li, Le Tian, Wenyu Jiang, Bai Lin
article en

Abstract

Enhancing the failure tolerance ability of networks is crucial, as node or link failures are common occurrences on-site. The current fault tolerance schemes are divided into reactive and proactive schemes. The reactive scheme requires detection and repair after the failure occurs, which may lead to long-term network interruptions. The proactive scheme can reduce recovery time through preset backup paths, but requires additional resources. Aiming at the problems of long recovery time or high overhead of the current failure tolerance schemes, the Polymorphic Network adopts field-definable network baseline technology, which can support diversified addressing and routing capabilities, making it possible to implement a more complex and efficient failure tolerance scheme. Inspired by this, we propose an efficient Multi-topology Failure Tolerance mechanism in Polymorphic Network (MFT-PN). The MFT-PN embeds a failure recovery function into the packet processing logic by leveraging the full programmable characteristics of the network element, improving failure recovery efficiency. The backup path information is pushed into the header of the failed packet to reduce the flow table storage overhead. Meanwhile, MFT-PN introduces the concept of multi-topology routing by constructing multiple logical topologies, with each topology adopting different failure recovery strategies. Then, we design a multi-topology loop-free link backup algorithm to calculate the backup path for each topology, providing extensive coverage for different failure scenarios. Experimental results show that compared with the existing strategies, MFT-PN can reduce resource overhead by over 72% and the packet loss rate by over 59%, as well as effectively cope with multiple failure scenarios.

ElectronicsVol. 14(18)
PLA Information Engineering University (CN), Academy of Military Medical Sciences (CN), Intelligent Decision Systems (Spain) (ES)
National Natural Science Foundation of China
Openalex Percentile: Top 72%
Software-Defined Networks and 5G
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