Deep-RMSA: A Deep-Reinforcement-Learning Routing, Modulation and Spectrum Assignment Agent for Elastic Optical Networks
Authors:
- Xiaoliang ChenXCXiaoliang Chen
- S. J. B. YooSYS. J. B. Yoo
- 1 January 2018
- conference paper
- Published by Optica Publishing Group
- p. W4F.2
Abstract
This paper demonstrates Deep-RMSA, a deep reinforcement learning based self-learning RMSA agent that can learn successful policies from dynamic network operations while realizing cognitive and autonomous RMSA in EONs.Keywords
All Related Versions
This publication has 4 references indexed in Scilit:
- On the Distance Spectrum Assignment in Elastic Optical NetworksIEEE/ACM Transactions on Networking, 2017
- Incentive-Driven Bidding Strategy for Brokers to Compete for Service Provisioning Tasks in Multi-Domain SD-EONsJournal of Lightwave Technology, 2016
- Human-level control through deep reinforcement learningNature, 2015
- Dynamic Service Provisioning in Elastic Optical Networks With Hybrid Single-/Multi-Path RoutingJournal of Lightwave Technology, 2012