Approaches to dynamic provisioning in multiband elastic optical networks

A. Beghelli, P. Morales, E. Viera, N. Jara, D. Borquez-Paredes, A. Leiva, G. Saavedra

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Adopting multiband transmission in optical networks can cost-effectively increase network capacity without deploying new fibre. In this paper, we focus on the solutions explored by the research community to address the problem of resource allocation in dynamic multiband elastic optical networks. We start by summarising the main challenges and contributions of the design of ad-hoc heuristics. Next, we review the few recent approaches based on deep reinforcement learning and evaluate the efficacy of different techniques to improve their performance. We also discuss possible future directions for research in the area.

Original languageEnglish
Title of host publicationProceedings of the 2023 International Conference on Optical Network Design and Modeling, ONDM 2023
EditorsTeresa Gomes, David Larrabeiti-Lopez, Carmen Mas-Machuca, Luca Valcarenghi, Luisa Jorge, Paulo Melo
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9783903176546
StatePublished - 2023
Externally publishedYes
Event2023 International Conference on Optical Network Design and Modeling, ONDM 2023 - Coimbra, Portugal
Duration: 8 May 202311 May 2023

Publication series

NameProceedings of the 2023 International Conference on Optical Network Design and Modeling, ONDM 2023

Conference

Conference2023 International Conference on Optical Network Design and Modeling, ONDM 2023
Country/TerritoryPortugal
CityCoimbra
Period8/05/2311/05/23

Keywords

  • Heuristics
  • Multiband optical networks
  • Reinforcement Learning
  • elastic optical networks

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