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TCP ex machina: computer-generated congestion control

Authors:

Keith Winstein,

Hari BalakrishnanAuthors Info & Claims

SIGCOMM '13: Proceedings of the ACM SIGCOMM 2013 conference on SIGCOMM

Pages 123 - 134

https://doi.org/10.1145/2486001.2486020

Published: 27 August 2013 Publication History

Abstract

This paper describes a new approach to end-to-end congestion control on a multi-user network. Rather than manually formulate each endpoint's reaction to congestion signals, as in traditional protocols, we developed a program called Remy that generates congestion-control algorithms to run at the endpoints.

In this approach, the protocol designer specifies their prior knowledge or assumptions about the network and an objective that the algorithm will try to achieve, e.g., high throughput and low queueing delay. Remy then produces a distributed algorithm---the control rules for the independent endpoints---that tries to achieve this objective.

In simulations with ns-2, Remy-generated algorithms outperformed human-designed end-to-end techniques, including TCP Cubic, Compound, and Vegas. In many cases, Remy's algorithms also outperformed methods that require intrusive in-network changes, including XCP and Cubic-over-sfqCoDel (stochastic fair queueing with CoDel for active queue management).

Remy can generate algorithms both for networks where some parameters are known tightly a priori, e.g. datacenters, and for networks where prior knowledge is less precise, such as cellular networks. We characterize the sensitivity of the resulting performance to the specificity of the prior knowledge, and the consequences when real-world conditions contradict the assumptions supplied at design-time.

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Index Terms

TCP ex machina: computer-generated congestion control
1. Networks
  1. Network protocols

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Published In

cover image ACM Conferences

SIGCOMM '13: Proceedings of the ACM SIGCOMM 2013 conference on SIGCOMM

August 2013

580 pages

ISBN:9781450320566

DOI:10.1145/2486001

General Chairs:
Dah Ming Chiu
Chinese University of Hong Kong, China
,
Jia Wang
AT&T Labs - Research, USA
,
Program Chairs:
Paul Barford
University of Wisconsin, USA
,
Srinivasan Seshan
Carnegie Mellon University, USA

ACM SIGCOMM Computer Communication Review Volume 43, Issue 4
October 2013
595 pages
ISSN:0146-4833
DOI:10.1145/2534169
Issue’s Table of Contents

Copyright © 2013 ACM.

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 the author(s) 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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New York, NY, United States

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Published: 27 August 2013

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SIGCOMM'13: ACM SIGCOMM 2013 Conference

August 12 - 16, 2013

Hong Kong, China

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SIGCOMM '13 Paper Acceptance Rate 38 of 246 submissions, 15%;

Overall Acceptance Rate 462 of 3,389 submissions, 14%

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Cited By

Yi FWan HJamieson KRexford JXie YMichel O(2024)Athena: Seeing and Mitigating Wireless Impact on Video Conferencing and BeyondProceedings of the 23rd ACM Workshop on Hot Topics in Networks10.1145/3696348.3696889(103-110)Online publication date: 18-Nov-2024
https://dl.acm.org/doi/10.1145/3696348.3696889
Zhang Hzhuo LLi HZhou AWang CMa HCai JKankanhalli MPrabhakaran BBoll SSubramanian RZheng LSingh VCesar PXie LXu D(2024)AraLive: Automatic Reward Adaption for Learning-based Live Video StreamingProceedings of the 32nd ACM International Conference on Multimedia10.1145/3664647.3681499(11099-11108)Online publication date: 28-Oct-2024
https://dl.acm.org/doi/10.1145/3664647.3681499
Ware RPhilip AHungria NKothari YSherry JSeshan SSekar VYu MSeneviratne AVeitch D(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
https://dl.acm.org/doi/10.1145/3651890.3672255
Ferreira MWare RKothari YLynce IMartins RNarayan ASherry JVallina-Rodríguez NSuarez-Tángil GLevin DPelsser C(2024)Reverse-Engineering Congestion Control Algorithm BehaviorProceedings of the 2024 ACM on Internet Measurement Conference10.1145/3646547.3688443(401-414)Online publication date: 4-Nov-2024
https://dl.acm.org/doi/10.1145/3646547.3688443
Liao XTian HZeng CWan XChen K(2024)Astraea: Towards Fair and Efficient Learning-based Congestion ControlProceedings of the Nineteenth European Conference on Computer Systems10.1145/3627703.3650069(99-114)Online publication date: 22-Apr-2024
https://dl.acm.org/doi/10.1145/3627703.3650069
Zhang HZhou AWang GLi CMa H(2024)Toward Optimal Live Video Streaming QoE: A Deep Feature-Fusion ApproachIEEE/ACM Transactions on Networking10.1109/TNET.2024.335183232:3(2360-2375)Online publication date: Jun-2024
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Tian HLiao XZeng CSun DZhang JChen K(2024)Efficient DRL-Based Congestion Control With Ultra-Low OverheadIEEE/ACM Transactions on Networking10.1109/TNET.2023.333073732:3(1888-1903)Online publication date: Jun-2024
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Jiang WLi HWu JLiu ZHuang JShan DWang J(2024)Improvement of Copa: Behaviors and Friendliness of Delay-Based Congestion Control AlgorithmIEEE/ACM Transactions on Networking10.1109/TNET.2023.327867732:1(127-142)Online publication date: Feb-2024
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Shan DJiang LZhang PJiang WLi HTang YRen F(2024)Enforcing Fairness in the Traffic Policer Among Heterogeneous Congestion Control AlgorithmsIEEE/ACM Transactions on Networking10.1109/TNET.2023.327641032:1(34-49)Online publication date: Feb-2024
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