Performance Prediction of Established Lightpaths Using Machine Learning and Field Data

Christine Tremblay

doi:10.1364/CLEOPR.2020.C1F_2

14th Pacific Rim Conference on Lasers and Electro-Optics (CLEO PR 2020)
OSA Technical Digest (Optica Publishing Group, 2020),
paper C1F_2
•https://doi.org/10.1364/CLEOPR.2020.C1F_2

Performance Prediction of Established Lightpaths Using Machine Learning and Field Data

Christine Tremblay

Conference on Lasers and Electro-Optics/Pacific Rim 2020

Sydney Australia
3–5 August 2020
ISBN: 978-0-646-82504-5

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Optical Networking for Metro and Data Centres (C1F)

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C. Tremblay, "Performance Prediction of Established Lightpaths Using Machine Learning and Field Data," in 14th Pacific Rim Conference on Lasers and Electro-Optics (CLEO PR 2020), OSA Technical Digest (Optica Publishing Group, 2020), paper C1F_2.

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Abstract

In this presentation, we explore machine learning models based on recurrent neural networks trained with field data for lightpath performance prediction in coherent optical networks through some illustrative examples.

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