QoS-aware Network Self-management Architecture based on DRL and SDN for remote areas

Juan Chafla Altamirano, Mohamd Amine Slimane, Hassan Hassan, Khalil Drira

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

Solving the problem of connectivity in remote areas is vital for providing important services (e.g., telemedicine, virtual education, etc.) to communities of these regions. However, managing these communication networks is complex and requires permanent human intervention in such inaccessible and highly variable environments. We propose a network self-management architecture based on SDN and DRL that self-adapts to operational conditions to meet the QoS demands of network services. We use a case study of QoS-aware routing optimization in a rural scenario to test our architecture.

Original languageEnglish
Title of host publication2022 IEEE 11th IFIP International Conference on Performance Evaluation and Modeling in Wireless and Wired Networks, PEMWN 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9783903176508
DOIs
StatePublished - 2022
Event11th IEEE IFIP International Conference on Performance Evaluation and Modeling in Wireless and Wired Networks, PEMWN 2022 - Rome, Italy
Duration: 8 Nov 202210 Nov 2022

Publication series

Name2022 IEEE 11th IFIP International Conference on Performance Evaluation and Modeling in Wireless and Wired Networks, PEMWN 2022

Conference

Conference11th IEEE IFIP International Conference on Performance Evaluation and Modeling in Wireless and Wired Networks, PEMWN 2022
Country/TerritoryItaly
CityRome
Period8/11/2210/11/22

Bibliographical note

Publisher Copyright:
© 2022 IFIP.

Keywords

  • Deep Reinforcement Learning
  • QoS
  • Routing Optimization
  • SDN
  • self-management

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