University of Oulu

Ruikun Wang, Jiawei Zhang, Shuangyi Yan, Chuidian Zeng, Hao Yu, Zhiqun Gu, Bojun Zhang, Tarik Taleb, and Yuefeng Ji, "Suspect fault screen assisted graph aggregation network for intra-/inter-node failure localization in ROADM-based optical networks," J. Opt. Commun. Netw. 15, C88-C99 (2023)

Suspect fault screen assisted graph aggregation network for intra-/inter-node failure localization in ROADM-based optical networks

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Author: Wang, Ruikun1; Zhang, Jiawei1; Yan, Shuangyi2;
Organizations: 1State Key Lab of Information Photonics and Optical Communications, Beijing University of Posts and Telecommunications (BUPT), Beijing, China
2High Performance Networks Group, Smart Internet Lab, University of Bristol, Bristol, UK
3Centre for Wireless Communications, University of Oulu, Oulu, Finland
Format: article
Version: accepted version
Access: embargoed
Persistent link: http://urn.fi/urn:nbn:fi-fe20231010139434
Language: English
Published: Optica Publishing Group, 2023
Publish Date: 2024-05-26
Description:

Abstract

In optical networks, failure localization is essential to stable operation and service restoration. Several approaches have been presented to achieve accurate failure localization of nodes and inter-nodes. However, due to increasing traffic and demand for flexibility, the reconfigurable optical add/drop multiplexer (ROADM) is evolving towards a multi-degree architecture. Therefore, each ROADM is composed of multiple devices, which makes intra-node failures become more complex. In this context, intra-node failure localization can effectively reduce the pressure on network operators to further find specific devices. In this work, we redefine the intra-/inter-node failure model for multi-degree ROADM-based optical networks and propose a suspect fault screen assisted graph aggregation network (SFS-GRN) for intra-/inter-node failure localization. The SFS is responsible for screening out suspect fault devices from all devices and reducing the number of candidate devices. The GRN is used to analyze these monitoring data from an optical performance monitoring (OPM) node and network wide and to determine the most likely failure device. The proposed scheme is evaluated in a nine-node simulated network and three-node testbed network. Extensive results show that the SFS-GRN achieves higher accuracy compared with existing methods under different percentages of OPM deployment, numbers of service requests, and failure types. The SFS can remove more than 98% of devices, which is beneficial to further detection and repair for network operators. Moreover, the proposed strategy takes about 10 ms to detect a potential failure, and it has the potential to be applied to a real scenario.

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Series: Journal of optical communications and networking
ISSN: 1943-0620
ISSN-E: 1943-0639
ISSN-L: 1943-0620
Volume: 15
Issue: 7
Pages: C88 - C99
DOI: 10.1364/JOCN.480970
OADOI: https://oadoi.org/10.1364/JOCN.480970
Type of Publication: A1 Journal article – refereed
Field of Science: 213 Electronic, automation and communications engineering, electronics
Subjects:
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