Demonstration of ML-aided impairment-aware L0 path computation in fully disaggregated multi-vendor optical transport networks

Huy Tran Quang; Quan Pham-Van; Dominique Verchere; Huu Trung Thieu; Djamal Zeghlache

Demonstration of ML-aided impairment-aware L0 path computation in fully disaggregated multi-vendor optical transport networks

Huy Tran Quang
, Quan Pham-Van
, Dominique Verchere
, Huu Trung Thieu
, Djamal Zeghlache

Bell Labs

Résultats de recherche: Contribution à un journal › Article de conférence › Revue par des pairs

Résumé

We demonstrate an online impairment-aware L0 path computation capability leveraging a machine learning model to recommend the most appropriate path and optical parameters combination for a connectivity service request in the fully disaggregated multi-vendor optical transport network.

langue originale	Anglais
journal	Optics InfoBase Conference Papers
état	Publié - 1 janv. 2021
Evénement	Optical Fiber Communication Conference, OFC 2021 - Virtual, Online, États-Unis Durée: 6 juin 2021 → 11 juin 2021

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@article{121e0a4a844b4aeba2f4191c6e30d8fe,

title = "Demonstration of ML-aided impairment-aware L0 path computation in fully disaggregated multi-vendor optical transport networks",

abstract = "We demonstrate an online impairment-aware L0 path computation capability leveraging a machine learning model to recommend the most appropriate path and optical parameters combination for a connectivity service request in the fully disaggregated multi-vendor optical transport network.",

author = "Quang, \{Huy Tran\} and Quan Pham-Van and Dominique Verchere and Thieu, \{Huu Trung\} and Djamal Zeghlache",

note = "Publisher Copyright: {\textcopyright} OSA 2021, {\textcopyright} 2021 The Author(s); Optical Fiber Communication Conference, OFC 2021 ; Conference date: 06-06-2021 Through 11-06-2021",

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AU - Quang, Huy Tran

AU - Pham-Van, Quan

AU - Verchere, Dominique

AU - Thieu, Huu Trung

AU - Zeghlache, Djamal

PY - 2021/1/1

Y1 - 2021/1/1

N2 - We demonstrate an online impairment-aware L0 path computation capability leveraging a machine learning model to recommend the most appropriate path and optical parameters combination for a connectivity service request in the fully disaggregated multi-vendor optical transport network.

AB - We demonstrate an online impairment-aware L0 path computation capability leveraging a machine learning model to recommend the most appropriate path and optical parameters combination for a connectivity service request in the fully disaggregated multi-vendor optical transport network.

UR - https://www.scopus.com/pages/publications/85133765410

M3 - Conference article

AN - SCOPUS:85133765410

SN - 2162-2701

JO - Optics InfoBase Conference Papers

JF - Optics InfoBase Conference Papers

T2 - Optical Fiber Communication Conference, OFC 2021

Y2 - 6 June 2021 through 11 June 2021

ER -

Demonstration of ML-aided impairment-aware L0 path computation in fully disaggregated multi-vendor optical transport networks

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