Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group

Field Trial of Machine-Learning-Assisted and SDN-Based Optical Network Management

Not Accessible

Your library or personal account may give you access

Abstract

In this paper, we reported machine-learning based network dynamic abstraction over a field-trial testbed. The implemented network-scale NCMDB allows the ML-based quality-of-transmission predictor abstract dynamic link parameters for further network planning.

© 2019 The Author(s)

PDF Article
More Like This
Field Trial of a Novel SDN Enabled Network Restoration Utilizing In-Depth Optical Performance Monitoring Assisted Network Re-Planning

F. Meng, Y. Ou, S. Yan, K. Sideris, M. D. G. Pascual, R. Nejabati, and D. Simeonidou
Th1J.8 Optical Fiber Communication Conference (OFC) 2017

Fault Management Based on Machine Learning [Invited]

Luis Velasco and Danish Rafique
W3G.3 Optical Fiber Communication Conference (OFC) 2019

Joint Optimization of Packet and Optical layers of a Core Network Using SDN Controller, CD ROADMs and machine-learning-based traffic prediction

Gagan Choudhury, Gaurav Thakur, and Simon Tse
M2A.1 Optical Fiber Communication Conference (OFC) 2019

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All Rights Reserved