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An overview of ML-based applications for next generation optical networks
- Source :
- Science China Information Sciences. 63
- Publication Year :
- 2020
- Publisher :
- Springer Science and Business Media LLC, 2020.
-
Abstract
- Over the past few decades, the demand for the capacity and reliability of optical networks has continued to grow. In the meantime, optical networks with larger knowledge scales have become sources of numerous heterogeneous data. In order to handle these new challenges, many issues need to be resolved, among which the low-margin optical networks design, power optimization, routing and wavelength assignment (RWA), failure management are quite important. However, the use of traditional algorithms in the above four applications shows some shortcomings. Fortunately, artificial intelligence (AI), especially machine learning (ML), is regarded as one of the most promising methods to overcome these shortcomings. In this study, we review the applications of ML methods in solving these four issues. Although many ML-based researches have emerged, the applications of ML techniques in optical networks still face challenges. Therefore, we also discuss some possible future directions of investigating ML-based approaches in optical networks.
- Subjects :
- Routing and wavelength assignment
General Computer Science
Computer science
Reliability (computer networking)
Failure management
Distributed computing
Still face
0202 electrical engineering, electronic engineering, information engineering
020207 software engineering
02 engineering and technology
Power optimization
Subjects
Details
- ISSN :
- 18691919 and 1674733X
- Volume :
- 63
- Database :
- OpenAIRE
- Journal :
- Science China Information Sciences
- Accession number :
- edsair.doi...........a32934c311d452e31e3686bece8e491f