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Machine Learning Algorithms for Prediction of the Quality of Transmission in Optical Networks

Increasing demand in the backbone Dense Wavelength Division (DWDM) Multiplexing network traffic prompts an introduction of new solutions that allow increasing the transmission speed without significant increase of the service cost. In order to achieve this objective simpler and faster, DWDM network...

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Autores principales: Kozdrowski, Stanisław, Cichosz, Paweł, Paziewski, Piotr, Sujecki, Sławomir
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7822106/
https://www.ncbi.nlm.nih.gov/pubmed/33375082
http://dx.doi.org/10.3390/e23010007
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author Kozdrowski, Stanisław
Cichosz, Paweł
Paziewski, Piotr
Sujecki, Sławomir
author_facet Kozdrowski, Stanisław
Cichosz, Paweł
Paziewski, Piotr
Sujecki, Sławomir
author_sort Kozdrowski, Stanisław
collection PubMed
description Increasing demand in the backbone Dense Wavelength Division (DWDM) Multiplexing network traffic prompts an introduction of new solutions that allow increasing the transmission speed without significant increase of the service cost. In order to achieve this objective simpler and faster, DWDM network reconfiguration procedures are needed. A key problem that is intrinsically related to network reconfiguration is that of the quality of transmission assessment. Thus, in this contribution a Machine Learning (ML) based method for an assessment of the quality of transmission is proposed. The proposed ML methods use a database, which was created only on the basis of information that is available to a DWDM network operator via the DWDM network control plane. Several types of ML classifiers are proposed and their performance is tested and compared for two real DWDM network topologies. The results obtained are promising and motivate further research.
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spelling pubmed-78221062021-02-24 Machine Learning Algorithms for Prediction of the Quality of Transmission in Optical Networks Kozdrowski, Stanisław Cichosz, Paweł Paziewski, Piotr Sujecki, Sławomir Entropy (Basel) Article Increasing demand in the backbone Dense Wavelength Division (DWDM) Multiplexing network traffic prompts an introduction of new solutions that allow increasing the transmission speed without significant increase of the service cost. In order to achieve this objective simpler and faster, DWDM network reconfiguration procedures are needed. A key problem that is intrinsically related to network reconfiguration is that of the quality of transmission assessment. Thus, in this contribution a Machine Learning (ML) based method for an assessment of the quality of transmission is proposed. The proposed ML methods use a database, which was created only on the basis of information that is available to a DWDM network operator via the DWDM network control plane. Several types of ML classifiers are proposed and their performance is tested and compared for two real DWDM network topologies. The results obtained are promising and motivate further research. MDPI 2020-12-22 /pmc/articles/PMC7822106/ /pubmed/33375082 http://dx.doi.org/10.3390/e23010007 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Kozdrowski, Stanisław
Cichosz, Paweł
Paziewski, Piotr
Sujecki, Sławomir
Machine Learning Algorithms for Prediction of the Quality of Transmission in Optical Networks
title Machine Learning Algorithms for Prediction of the Quality of Transmission in Optical Networks
title_full Machine Learning Algorithms for Prediction of the Quality of Transmission in Optical Networks
title_fullStr Machine Learning Algorithms for Prediction of the Quality of Transmission in Optical Networks
title_full_unstemmed Machine Learning Algorithms for Prediction of the Quality of Transmission in Optical Networks
title_short Machine Learning Algorithms for Prediction of the Quality of Transmission in Optical Networks
title_sort machine learning algorithms for prediction of the quality of transmission in optical networks
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7822106/
https://www.ncbi.nlm.nih.gov/pubmed/33375082
http://dx.doi.org/10.3390/e23010007
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