Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group
Conferences > ACPC > 2020 > M4A > M4A.196
  • Asia Communications and Photonics Conference/International Conference on Information Photonics and Optical Communications 2020 (ACP/IPOC)
  • OSA Technical Digest (Optica Publishing Group, 2020),
  • paper M4A.196
  • •https://doi.org/10.1364/ACPC.2020.M4A.196

Reconfigurable Network Topology Based on Deep Reinforcement Learning in Software-Defined Data-Center Networks

Wen Yang, Bingli Guo, Yu Shang, and Shanguo Huang

Not Accessible

Your library or personal account may give you access

Abstract

In this paper, a Deep-Reinforcement Learning (DRL) agent is implemented and evaluated to enable dynamic topology reconfiguration according to traffic fluctuations and proposes to minimize the network delay.

© 2020 The Author(s)

PDF Article
More Like This
Machine-Learning-Aided Bandwidth and Topology Reconfiguration for Optical Data Center Networks

Roberto Proietti, Che-Yu Liu, Xiaoliang Chen, and S.J.Ben Yoo
W4A.4 Optical Fiber Communication Conference (OFC) 2021

DeepAutonet: Self-driving Reconfigurable HPC System with Deep Reinforcement Learning

Yu Shang, Xiaoliang Chen, Roberto Proietti, Bingli Guo, Shanguo Huang, and S. J. Ben Yoo
S3C.4 Asia Communications and Photonics Conference (ACP) 2019

Routing Based On Deep Reinforcement Learning In Optical Transport Networks

José Suárez-Varela, Albert Mestres, Junlin Yu, Li Kuang, Haoyu Feng, Pere Barlet-Ros, and Albert Cabellos-Aparicio
M2A.6 Optical Fiber Communication Conference (OFC) 2019

View More...
Select as filters
Select Topics Cancel
Top
       
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.
Privacy | Terms of Use