Demonstration of ML-Assisted Soft-Failure Localization Based on Network Digital Twins-Reference-Cited by-同舟云学术

Demonstration of ML-Assisted Soft-Failure Localization Based on Network Digital Twins

Published:2022-07-15 Issue:14 Volume:40 Page:4514-4520
ISSN:0733-8724
Container-title:Journal of Lightwave Technology
language:
Short-container-title:J. Lightwave Technol.

Author:

Mayer Kayol S.¹^ORCID,Pinto Rossano P.¹,Soares Jonathan A.¹,Arantes Dalton S.¹,Rothenberg Christian E.¹^ORCID,Cavalcante Vinicius²,Santos Leonardo L.²,Moraes Filipe D.²,Mello Darli A. A.¹^ORCID

Affiliation:

1. School of Electrical and Computer Engineering – FEEC, University of Campinas – Unicamp, Campinas, Brazil

2. Padtec S/A, Campinas, Brazil

Funder

Coordenao de Aperfeioamento de Pessoal de Nvel Superior

Padtec SA

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Atomic and Molecular Physics, and Optics

Link

http://xplorestaging.ieee.org/ielx7/50/9826878/09763325.pdf?arnumber=9763325

Reference45 articles.

1. Soft-Failure Localization and Time-Dependent Degradation Detection for Network Diagnosis

2. Quality of transmission estimator retraining for dynamic optimization in optical networks

3. Lightweight Network-Wide Telemetry Without Explicitly Using Probe Packets

4. Domain adaptation and transfer learning for failure detection and failure-cause identification in optical networks across different lightpaths [Invited]

5. Dual-Stage Soft Failure Detection and Identification for Low-Margin Elastic Optical Network by Exploiting Digital Spectrum Information

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