Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group
  • Asia Communications and Photonics Conference (ACPC) 2019
  • OSA Technical Digest (Optica Publishing Group, 2019),
  • paper S3C.4

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

Not Accessible

Your library or personal account may give you access

Abstract

We design and evaluate DeepAutonet, a self-driving reconfigurable network exploiting deep reinforcement learning. Simulation results show that DeepAutonet can adapt its topology automatically to different traffic conditions with up to 1.9x latency reduction.

© 2019 The Author(s)

PDF Article
More Like This
Reconfigurable Network Topology Based on Deep Reinforcement Learning in Software-Defined Data-Center Networks

Wen Yang, Bingli Guo, Yu Shang, and Shanguo Huang
M4A.196 Asia Communications and Photonics Conference (ACP) 2020

Deep-NFVOrch: Deep Reinforcement Learning based Service Framework for Adaptive vNF Service Chaining in IDC-EONs

Baojia Li, Wei Lu, and Zuqing Zhu
Th1H.2 Optical Fiber Communication Conference (OFC) 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

Select as filters


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