This Special Issue contains a collection of outstanding papers covering several applications of machine learning in optical communications and networking, including: resource management in elastic optical networks, datacenters and ROADM-based networks; noise and signal-quality estimation; and traffic prediction. We provide a brief overview of the current state of machine learning in optical networks, followed by a categorization of the eleven papers in this special issue.

© 2018 Optical Society of America

Full Article  |  PDF Article
OSA Recommended Articles
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)

Machine-Learning-Based Prediction for Resource (Re)allocation in Optical Data Center Networks

Sandeep Kumar Singh and Admela Jukan
J. Opt. Commun. Netw. 10(10) D12-D28 (2018)

SOON: self-optimizing optical networks with machine learning

Yongli Zhao, Boyuan Yan, Dongmei Liu, Yongqi He, Dajiang Wang, and Jie Zhang
Opt. Express 26(22) 28713-28726 (2018)

Cited By

OSA participates in Crossref's Cited-By Linking service. Citing articles from OSA journals and other participating publishers are listed here.

Alert me when this article is cited.