Automation of multi-layer multi-domain transport networks and the role of AI [Invited]

With increasing demand for customized connectivity, transport networks must evolve towards autonomous and customer-driven network management. This paper presents a comprehensive overview of network autonomy and the challenges associated with evolving toward higher levels of autonomy. Moreover, various use cases of artificial intelligence in network automation in IP-over-DWDM transport networks are also analyzed, in particular related to traffic prediction, quality of transmission, anomaly detection, network planning, and proactive failure management. Additionally, the role of generative AI in network operation is explored. Central to our discussion is a proposed control architecture based on open and standard SDN APIs, which incorporates network slicing for multi-layer transport networks and enables real-time access to normalized data, facilitating autonomous network operation.

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Publication Details

Journal
Journal of Optical Communications and Networking
Published
2024-10-16
DOI
https://doi.org/10.1364/jocn.537463
Citations
8
Primary Topic
Advanced Research in Systems and Signal Processing
Type
article
Field-Weighted Citation Impact
2.63

Funders

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article

Automation of multi-layer multi-domain transport networks and the role of AI [Invited]

Ramon Duran Barroso, A. Costa, Liesbeth Roelens, Óscar González de Dios et al.
8 citations
Journal of Optical Communications and Networking
Advanced Research in Systems and Signal Processing
2.63
article

Automation of multi-layer multi-domain transport networks and the role of AI [Invited]

Ramon Duran Barroso, A. Costa, Liesbeth Roelens, Óscar González de Dios, Ignacio de Miguel, Pablo Armingol Robles, Juan Pedro Fernández-Palacios Giménez
article en
8 citations

Abstract

With increasing demand for customized connectivity, transport networks must evolve towards autonomous and customer-driven network management. This paper presents a comprehensive overview of network autonomy and the challenges associated with evolving toward higher levels of autonomy. Moreover, various use cases of artificial intelligence in network automation in IP-over-DWDM transport networks are also analyzed, in particular related to traffic prediction, quality of transmission, anomaly detection, network planning, and proactive failure management. Additionally, the role of generative AI in network operation is explored. Central to our discussion is a proposed control architecture based on open and standard SDN APIs, which incorporates network slicing for multi-layer transport networks and enables real-time access to normalized data, facilitating autonomous network operation.

Journal of Optical Communications and NetworkingVol. 17(2)
Universidad de Valladolid (ES)
Ministerio de Ciencia, Innovación y Universidades, Horizon 2020 Framework Programme, Agencia Estatal de Investigación, H2020 Marie Skłodowska-Curie Actions
Openalex Percentile: Top 10%
Advanced Research in Systems and Signal Processing
2.63
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