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The Great Internet TCP Congestion Control Census

Published: 17 December 2019 Publication History

Abstract

In 2016, Google proposed and deployed a new TCP variant called BBR. BBR represents a major departure from traditional congestion-window-based congestion control. Instead of using loss as a congestion signal, BBR uses estimates of the bandwidth and round-trip delays to regulate its sending rate. The last major study on the distribution of TCP variants on the Internet was done in 2011, so it is timely to conduct a new census given the recent developments around BBR. To this end, we designed and implemented Gordon, a tool that allows us to measure the exact congestion window (cwnd) corresponding to each successive RTT in the TCP connection response of a congestion control algorithm. To compare a measured flow to the known variants, we created a localized bottleneck where we can introduce a variety of network changes like loss events, bandwidth change, and increased delay, and normalize all measurements by RTT. An offline classifier is used to identify the TCP variant based on the cwnd trace over time. Our results suggest that CUBIC is currently the dominant TCP variant on the Internet, and it is deployed on about 36% of the websites in the Alexa Top 20,000 list. While BBR and its variant BBR G1.1 are currently in second place with a 22% share by website count, their present share of total Internet traffic volume is estimated to be larger than 40%. We also found that Akamai has deployed a unique loss-agnostic rate-based TCP variant on some 6% of the Alexa Top 20,000 websites and there are likely other undocumented variants. The traditional assumption that TCP variants "in the wild" will come from a small known set is not likely to be true anymore. We predict that some variant of BBR seems poised to replace CUBIC as the next dominant TCP variant on the Internet.

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  • (2024)Prudentia: Findings of an Internet Fairness WatchdogProceedings of the ACM SIGCOMM 2024 Conference10.1145/3651890.3672229(506-520)Online publication date: 4-Aug-2024
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Published In

cover image Proceedings of the ACM on Measurement and Analysis of Computing Systems
Proceedings of the ACM on Measurement and Analysis of Computing Systems  Volume 3, Issue 3
SIGMETRICS
December 2019
525 pages
EISSN:2476-1249
DOI:10.1145/3376928
Issue’s Table of Contents
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 17 December 2019
Published in POMACS Volume 3, Issue 3

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  1. congestion control
  2. measurement study

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  • Singapore NRF

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Cited By

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  • (2024)CCAnalyzer: An Efficient and Nearly-Passive Congestion Control ClassifierProceedings of the ACM SIGCOMM 2024 Conference10.1145/3651890.3672255(181-196)Online publication date: 4-Aug-2024
  • (2024)Prudentia: Findings of an Internet Fairness WatchdogProceedings of the ACM SIGCOMM 2024 Conference10.1145/3651890.3672229(506-520)Online publication date: 4-Aug-2024
  • (2024)Keeping an Eye on Congestion Control in the Wild with NebbyProceedings of the ACM SIGCOMM 2024 Conference10.1145/3651890.3672223(136-150)Online publication date: 4-Aug-2024
  • (2024)Dragonfly: In-Flight CCA IdentificationIEEE Transactions on Network and Service Management10.1109/TNSM.2024.338041721:3(2675-2685)Online publication date: 1-Jun-2024
  • (2024)P4BS: Leveraging Passive Measurements From P4 Switches to Dynamically Modify a Router’s Buffer SizeIEEE Transactions on Network and Service Management10.1109/TNSM.2023.330633521:1(1082-1099)Online publication date: 1-Feb-2024
  • (2024)Fairness Improvement of Different TCP Congestion Control Algorithms Using P4 Programmable Data Plane2024 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM)10.1109/PACRIM61180.2024.10690198(1-6)Online publication date: 21-Aug-2024
  • (2024)Machine learning-based estimation of the number of competing flows at a bottleneck linkNOMS 2024-2024 IEEE Network Operations and Management Symposium10.1109/NOMS59830.2024.10574929(1-4)Online publication date: 6-May-2024
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  • (2024)BBR vs. BBRv2: A Performance Evaluation2024 16th International Conference on COMmunication Systems & NETworkS (COMSNETS)10.1109/COMSNETS59351.2024.10427175(379-387)Online publication date: 3-Jan-2024
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