Analyzing vulnerability of optical fiber network considering recoverability

Ke Wang, Jinfeng Liu, Lai Tian, Xianfeng Tan, Guansheng Peng, Tianwen Qin and Jun Wu

Reliability Engineering and System Safety, 2022, vol. 221, issue C

Abstract: With the development of optical transmission technology, optical fiber networks have become critical infrastructures in supporting information transmission on the Internet. However, the fiber cable is very vulnerable to large-scale damage such as earthquakes or pulse bombs. What is more serious is that it will take a long time to locate and repair the damages on fiber links. The long-term repair process will cause continuous network performance degradation and severe economic loss. The fact is that these dangerous areas may be ignored by traditional vulnerability analysis models. To solve this problem, this paper proposes a method to analyze the vulnerability of fiber networks based on network recoverability. We first improve the traditional fiber network simulation methods and damage simulation methods to provide a compatible foundation for the network recoverability simulation. Then, we present the network vulnerability analysis model: the Damage Measurement and Location Model (DMLM). The model employs the heuristic traversal algorithm based on random points to locate the candidate attack positions. We design three vulnerability metrics: two metrics are related to network recoverability and one metric is used for comparison. We also build their corresponding theoretical frameworks to determine the appropriate model parameters to satisfy the specified estimation error requirements. Numerical results prove the proposed model’s effectiveness and excellent sensitivity for essential parameters. The visual results of the vulnerable zones prove the necessity of considering network recoverability in vulnerability analysis of optical fiber networks.

Keywords: Optical fiber network; Large-scale damage; Damage measurement; Recoverability; Vulnerability (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:221:y:2022:i:c:s095183202100778x

DOI: 10.1016/j.ress.2021.108308

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