The DOI matches its Crossref record; 29 of the 29 references it cites were found in a registry or an index.
Artificial intelligence (AI) methods in optical networks: A comprehensive survey
Open accessAbstract
Artificial intelligence (AI) is an extensive scientific discipline which enables computer systems to solve problems by emulating complex biological processes such as learning, reasoning and self-correction. This paper presents a comprehensive review of the application of AI techniques for improving performance of optical communication systems and networks. The use of AI-based techniques is first studied in applications related to optical transmission, ranging from the characterization and operation of network components to performance monitoring, mitigation of nonlinearities, and quality of transmission estimation. Then, applications related to optical network control and management are also reviewed, including topics like optical network planning and operation in both transport and access networks. Finally, the paper also presents a summary of opportunities and challenges in optical networking where AI is expected to play a key role in the near future.
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Cites
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A Survey on Software-Defined Networking
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Machine Learning Techniques in Optical Communication
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Cited by
Revolutionizing education with AI: Exploring the transformative potential of ChatGPT
Adiguzel, T., Kaya, M. H., & Cansu, F. K. (2023) · Contemporary Educational Technology · doi:10.30935/cedtech/13152 · Cited by 975
Artificial intelligence: a survey on evolution, models, applications and future trends
Lu, Y. (2019) · Journal of Management Analytics · doi:10.1080/23270012.2019.1570365 · Cited by 641
An Optical Communication's Perspective on Machine Learning and Its Applications
Khan, F. N., Fan, Q., Lu, C., & Lau, A. P. T. (2019) · Journal of Lightwave Technology · doi:10.1109/jlt.2019.2897313 · Cited by 316
Machine Learning for Network Automation: Overview, Architecture, and Applications [Invited Tutorial]
Rafique, D., & Velasco, L. (2018) · Journal of Optical Communications and Networking · doi:10.1364/jocn.10.00d126 · Cited by 298
Natalino, C., Schiano, M., Di Giglio, A., Wosinska, L., & Furdek, M. (2019) · Journal of Lightwave Technology · doi:10.1109/jlt.2019.2923558 · Cited by 63
Metadata
- Authors
- Mata, J., de Miguel, I., Durán, R. J., Merayo, N., Singh, S. K., Jukan, A., & Chamania, M.
- Venue
- Optical Switching and Networking
- Publisher
- Elsevier BV
- Published
- 2018-04
- Volume
- 28
- Pages
- 43-57
- ISSN
- 1573-4277 (ISSN-L)
- OpenAlex
- W2781788077
- Cited by
- 359
- References
- 29
- FWCI
- 17.69
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Mata, J., de Miguel, I., Durán, R. J., Merayo, N., Singh, S. K., Jukan, A., & Chamania, M. (2018). Artificial intelligence (AI) methods in optical networks: A comprehensive survey. Optical Switching and Networking. https://doi.org/10.1016/j.osn.2017.12.006
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
