DATE: Disturbance-Aware Traffic Engineering with Reinforcement Learning in Software-Defined Networks

Minghao Ye, Junjie Zhang, Zehua Guo, H. Jonathan Chao

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Traffic Engineering (TE) has been applied to optimize network performance by routing/rerouting flows based on traffic loads and network topologies. To cope with network dynamics from emerging applications, it is essential to reroute flows more frequently than today's TE to maintain network performance. However, existing TE solutions may introduce considerable Quality of Service (QoS) degradation and service disruption since they do not take the potential negative impact of flow rerouting into account. In this paper, we apply a new QoS metric named network disturbance to gauge the impact of flow rerouting while optimizing network load balancing in backbone networks. To employ this metric in TE design, we propose a disturbance-aware TE called DATE, which uses Reinforcement Learning (RL) to intelligently select some critical flows between nodes for each traffic matrix and reroute them using Linear Programming (LP) to jointly optimize network performance and disturbance. DATE is equipped with a customized actor-critic architecture and Graph Neural Networks (GNNs) to handle dynamic traffic and single link failures. Extensive evaluations show that DATE can outperform state-of-the-art TE methods with close-to-optimal load balancing performance while effectively mitigating the 99th percentile network disturbance by up to 31.6%.

Original languageEnglish (US)
Title of host publication2021 IEEE/ACM 29th International Symposium on Quality of Service, IWQOS 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665414944
DOIs
StatePublished - Jun 25 2021
Event29th IEEE/ACM International Symposium on Quality of Service, IWQOS 2021 - Virtual, Tokyo, Japan
Duration: Jun 25 2021Jun 28 2021

Publication series

Name2021 IEEE/ACM 29th International Symposium on Quality of Service, IWQOS 2021

Conference

Conference29th IEEE/ACM International Symposium on Quality of Service, IWQOS 2021
Country/TerritoryJapan
CityVirtual, Tokyo
Period6/25/216/28/21

Keywords

  • Link Failure
  • Network Disturbance
  • Reinforcement Learning
  • Routing
  • Software-Defined Networking
  • Traffic Engineering

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems and Management
  • Safety, Risk, Reliability and Quality

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