AMRT: Anti-ECN Marking to Improve Utilization of Receiver-driven Transmission in Data Center

Jinbin Hu, Jiawei Huang, Zhaoyi Li, Jianxin Wang, Tian He

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

6 Scopus citations

Abstract

Cloud applications generate a variety of workloads ranging from delay-sensitive flows to bandwidth-hungry ones in data centers. Existing reactive or proactive congestion control protocols are hard to simultaneously achieve ultra-low latency and high link utilization across all workloads in data center networks. We present a new receiver-driven transport scheme using anti-ECN (Explicit Congestion Notification) marking to achieve both near-zero queueing delay and full link utilization by reasonably increasing sending rate in the case of under-utilization. Specifically, switches mark the ECN bit of data packets once detecting spare bandwidth. When receiving the anti-ECN marked packet, the receiver generates the corresponding marked grant to trigger more data packets. The experimental results of small-scale testbed implementation and large-scale NS2 simulation show that AMRT effectively reduces the average flow completion time (AFCT) by up to 40.8% and improves the link utilization by up to 36.8% under high workload over the state-of-the-art receiver-driven transmission schemes.

Original languageEnglish (US)
Title of host publicationProceedings of the 49th International Conference on Parallel Processing, ICPP 2020
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450388160
DOIs
StatePublished - Aug 17 2020
Event49th International Conference on Parallel Processing, ICPP 2020 - Virtual, Online, Canada
Duration: Aug 17 2020Aug 20 2020

Publication series

NameACM International Conference Proceeding Series

Conference

Conference49th International Conference on Parallel Processing, ICPP 2020
Country/TerritoryCanada
CityVirtual, Online
Period8/17/208/20/20

Bibliographical note

Funding Information:
This work is supported by the National Natural Science Foundation of China (61872387, 61572530, 61872403), CERNET Innovation Project (Grant No. NGII20170107), Project of Foreign Cultural and Educational Expert (G20190018003).

Publisher Copyright:
© 2020 ACM.

Keywords

  • Data center
  • link utilization
  • receiver-driven

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