Dynamic modulation format and wavelength assignment in optical networks using reinforcement learning

Maria Freire-Hermelo; Antoine Lavignotte; Catherine Lepers

Dynamic modulation format and wavelength assignment in optical networks using reinforcement learning

Maria Freire-Hermelo
, Antoine Lavignotte
, Catherine Lepers

CNRS UMR 5157 SAMOVAR

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

Résumé

In this paper, we present the strategy we have adopted to reduce the adding or dropping channel blocking probability using reinforcement learning in comparison with other methods. We demonstrate 27 % reduction with 40 % channel load.

langue originale	Anglais
Numéro d'article	NeF2B.4
journal	Optics InfoBase Conference Papers
état	Publié - 1 janv. 2021
Evénement	Photonic Networks and Devices, Networks 2021 - Part of OSA Advanced Photonics Congress 2021 - Virtual, Online, États-Unis Durée: 26 juil. 2021 → 29 juil. 2021

Contient cette citation

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title = "Dynamic modulation format and wavelength assignment in optical networks using reinforcement learning",

abstract = "In this paper, we present the strategy we have adopted to reduce the adding or dropping channel blocking probability using reinforcement learning in comparison with other methods. We demonstrate 27 \% reduction with 40 \% channel load.",

author = "Maria Freire-Hermelo and Antoine Lavignotte and Catherine Lepers",

note = "Publisher Copyright: {\textcopyright}2021TheAuthor(s); Photonic Networks and Devices, Networks 2021 - Part of OSA Advanced Photonics Congress 2021 ; Conference date: 26-07-2021 Through 29-07-2021",

year = "2021",

month = jan,

day = "1",

language = "English",

journal = "Optics InfoBase Conference Papers",

issn = "2162-2701",

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T1 - Dynamic modulation format and wavelength assignment in optical networks using reinforcement learning

AU - Freire-Hermelo, Maria

AU - Lavignotte, Antoine

AU - Lepers, Catherine

PY - 2021/1/1

Y1 - 2021/1/1

N2 - In this paper, we present the strategy we have adopted to reduce the adding or dropping channel blocking probability using reinforcement learning in comparison with other methods. We demonstrate 27 % reduction with 40 % channel load.

AB - In this paper, we present the strategy we have adopted to reduce the adding or dropping channel blocking probability using reinforcement learning in comparison with other methods. We demonstrate 27 % reduction with 40 % channel load.

M3 - Conference article

AN - SCOPUS:85119486604

SN - 2162-2701

JO - Optics InfoBase Conference Papers

JF - Optics InfoBase Conference Papers

M1 - NeF2B.4

T2 - Photonic Networks and Devices, Networks 2021 - Part of OSA Advanced Photonics Congress 2021

Y2 - 26 July 2021 through 29 July 2021

ER -

Dynamic modulation format and wavelength assignment in optical networks using reinforcement learning

Résumé

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