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Adaptive-BBR: Fine-Grained Congestion Control with Improved Fairness and Low Latency

  • Ming Yang
  • , Peng Yang
  • , Chaozhun Wen
  • , Qiong Liu
  • , Jingjing Luo
  • , Li Yu
  • Huazhong University of Science and Technology
  • Harbin Institute of Technology Shenzhen

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

Abstract

Traditional loss-based congestion control protocols interpret packet loss as network congestion. Recently, Google proposed BBR, which is a congestion-based congestion control protocol. It employs delivery rate as the knob for congestion control, which achieves higher throughput and lower latency. Interestingly, BBR is found to have a preference for longer round-trip time (RTT) flows, which enjoy higher bandwidth ratio compared to flows with shorter RTT. To address this fairness issue, we proposed Adaptive-BBR, which creatively uses adaptive pacing gain to adjust the sending rate. The objective is that, via the proposed fine-grained adaptive mechanism, flows with different RTTs share similar portion of bottleneck bandwidth. Simulation results show that Adaptive-BBR can improve fairness by at least 47.8 %, and reduce average queuing delay by up to 93.3%, compared with that of BBR.

Original languageEnglish
Title of host publication2019 IEEE Wireless Communications and Networking Conference, WCNC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538676462
DOIs
StatePublished - Apr 2019
Externally publishedYes
Event2019 IEEE Wireless Communications and Networking Conference, WCNC 2019 - Marrakesh, Morocco
Duration: 15 Apr 201919 Apr 2019

Publication series

NameIEEE Wireless Communications and Networking Conference, WCNC
Volume2019-April
ISSN (Electronic)1558-2612

Conference

Conference2019 IEEE Wireless Communications and Networking Conference, WCNC 2019
Country/TerritoryMorocco
CityMarrakesh
Period15/04/1919/04/19

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