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

Machine-Learning-Aided Service Provisioning in Multi-Domain Optical Networks

Not Accessible

Your library or personal account may give you access

Abstract

This paper discusses testbed experiments and algorithms for machine-learning-aided service provisioning in multi-domain optical networks. Experimental results of hierarchical learning for QoT estimation of end-to-end lightpaths and a multi-agent DRL-based RMSA algorithm are presented.

© 2019 The Author(s)

PDF Article
More Like This
The First Testbed Demonstration of Cognitive End-to-End Optical Service Provisioning with Hierarchical Learning across Multiple Autonomous Systems

Gengchen Liu, Kaiqi Zhang, Xiaoliang Chen, Hongbo Lu, Jiannan Guo, Jie Yin, Roberto Proietti, Zuqing Zhu, and S. J. Ben Yoo
Th4D.7 Optical Fiber Communication Conference (OFC) 2018

Experimental Demonstration of Cognitive Provisioning and Alien Wavelength Monitoring in Multi-domain EON

R. Proietti, X. Chen, A. Castro, G. Liu, H. Lu, K. Zhang, J. Guo, Z. Zhu, L. Velasco, and S. J. B. Yoo
W4F.7 Optical Fiber Communication Conference (OFC) 2018

Multi-Agent Federated Reinforcement Learning for Privacy-enhanced Service Provision in Multi-domain Optical Network

Haiyu Liu, Rentao Gu, Zhekang Li, and Yuefeng Ji
T1C.3 Asia Communications and Photonics Conference (ACPC) 2021

References

You do not have subscription access to this journal. Citation lists with outbound citation links are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Select as filters


Select Topics Cancel
© Copyright 2022 | Optica Publishing Group. All Rights Reserved