A QoS-aware network reconfiguration method in data centers based on deep reinforcement learning

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Abstract

We demonstrate a dynamic network reconfiguration method (ACRO) based on deep reinforcement learning that can autonomously learn the scheme to reconfigure the application traffic with different QoS requirements. Numerical results based on real application traffics indicate that the ACRO provides up to 24.6% network latency improvement.

Original languageEnglish
Title of host publication45th European Conference on Optical Communication, ECOC 2019
PublisherInstitution of Engineering and Technology (IET)
ISBN (Electronic)9781839530074, 9781839530661, 9781839530883, 9781839530890, 9781839531071, 9781839531088, 9781839531255, 9781839531705, 9781839531859
Publication statusPublished - 2019
Event45th European Conference on Optical Communication, ECOC 2019 - Dublin, Ireland
Duration: 22 Sep 201926 Sep 2019
https://www.ecoc2019.org/

Publication series

NameIET Conference Publications
NumberCP765

Conference

Conference45th European Conference on Optical Communication, ECOC 2019
Abbreviated titleECOC 2019
CountryIreland
CityDublin
Period22/09/1926/09/19
Internet address

Keywords

  • Application traffic
  • Deep reinforcement learning
  • OMNET++
  • Optical network reconfiguration

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