Abstract

Network operators will require autonomous operation with the help of artificial intelligence to reduce operational expenditures and to create networks that are easier to manage and maintain. However, not all operators operate in the same way. Therefore, we may have different operator-specific use cases for such autonomous operations. Differences may arise from the range and variety of services and social and/or cultural difference/background. However, we believe that there should be a common framework to achieve such an autonomous world in network operation. We discuss such operator-specific use cases and requirements in this paper. Then, we propose a possible common network diagnosis framework (the CAT cycle) and its platform to meet the requirements.

© 2019 Optical Society of America

Machine Learning for Network Automation: Overview, Architecture, and Applications [Invited Tutorial]

Danish Rafique and Luis Velasco
J. Opt. Commun. Netw. 10(10) D126-D143 (2018)

Autonomous network diagnosis from the carrier perspective [Invited]: publisher’s note

Takafumi Tanaka, Akira Hirano, Shoukei Kobayashi, Takuya Oda, Seiki Kuwabara, Andrew Lord, Paul Gunning, Oscar Gonzalez de Dios, Victor Lopez, Arturo Mayoral Lopez de Lerma, and Antonio Manzalini
J. Opt. Commun. Netw. 12(3) 1-1 (2020)

Coordination between control layer AI and on-board AI in optical transport networks [Invited]

Yongli Zhao, Boyuan Yan, Zhuotong Li, Wei Wang, Ying Wang, and Jie Zhang
J. Opt. Commun. Netw. 12(1) A49-A57 (2020)

Autonomic Disaggregated Multilayer Networking

Lluís Gifre, Jose-Luis Izquierdo-Zaragoza, Marc Ruiz, and Luis Velasco
J. Opt. Commun. Netw. 10(5) 482-492 (2018)

Blockchain for the digital twin-driven autonomous optical network

Yue Pang, Min Zhang, Lifang Zhang, Jin Li, Wenbin Chen, Yidi Wang, and Danshi Wang
J. Opt. Commun. Netw. 16(3) 278-293 (2024)