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...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-12-01
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| Series: | Entropy |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1099-4300/23/1/7 |
| _version_ | 1797543816413052928 |
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| author | Stanisław Kozdrowski Paweł Cichosz Piotr Paziewski Sławomir Sujecki |
| author_facet | Stanisław Kozdrowski Paweł Cichosz Piotr Paziewski Sławomir Sujecki |
| author_sort | Stanisław Kozdrowski |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-03-10T13:51:17Z |
| format | Article |
| id | doaj.art-055b1b92244c4f73b482e9d228180208 |
| institution | Directory Open Access Journal |
| issn | 1099-4300 |
| language | English |
| last_indexed | 2024-03-10T13:51:17Z |
| publishDate | 2020-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Entropy |
| spelling | doaj.art-055b1b92244c4f73b482e9d2281802082023-11-21T02:04:19ZengMDPI AGEntropy1099-43002020-12-01231710.3390/e23010007Machine Learning Algorithms for Prediction of the Quality of Transmission in Optical NetworksStanisław Kozdrowski0Paweł Cichosz1Piotr Paziewski2Sławomir Sujecki3Computer Science Institute, Warsaw University of Technology, Nowowiejska 15/19, 00-665 Warsaw, PolandComputer Science Institute, Warsaw University of Technology, Nowowiejska 15/19, 00-665 Warsaw, PolandComputer Science Institute, Warsaw University of Technology, Nowowiejska 15/19, 00-665 Warsaw, PolandTelecommunications and Teleinformatics Department, Wroclaw University of Science and Technology, Wyb. Wyspianskiego 27, 50-370 Wroclaw, PolandIncreasing 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.https://www.mdpi.com/1099-4300/23/1/7artificial intelligencemachine learningoptical networksquality of transmissionmachine learning classifiers |
| spellingShingle | Stanisław Kozdrowski Paweł Cichosz Piotr Paziewski Sławomir Sujecki Machine Learning Algorithms for Prediction of the Quality of Transmission in Optical Networks Entropy artificial intelligence machine learning optical networks quality of transmission machine learning classifiers |
| 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 | artificial intelligence machine learning optical networks quality of transmission machine learning classifiers |
| url | https://www.mdpi.com/1099-4300/23/1/7 |
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