IDEAS home Printed from https://ideas.repec.org/a/gam/jftint/v16y2024i4p131-d1375735.html
   My bibliography  Save this article

Congestion Control Mechanism Based on Backpressure Feedback in Data Center Networks

Author

Listed:
  • Wei Li

    (College of Artificial Intelligence, North China University of Science and Technology, Tangshan 063210, China
    Hebei Provincial Key Laboratory of Industrial Intelligent Perception, North China University of Science and Technology, Tangshan 063210, China)

  • Mengzhen Ren

    (College of Artificial Intelligence, North China University of Science and Technology, Tangshan 063210, China)

  • Yazhi Liu

    (College of Artificial Intelligence, North China University of Science and Technology, Tangshan 063210, China)

  • Chenyu Li

    (College of Artificial Intelligence, North China University of Science and Technology, Tangshan 063210, China)

  • Hui Qian

    (College of Artificial Intelligence, North China University of Science and Technology, Tangshan 063210, China)

  • Zhenyou Zhang

    (College of Artificial Intelligence, North China University of Science and Technology, Tangshan 063210, China)

Abstract

In order to solve the congestion problem caused by the dramatic growth of traffic in data centers, many end-to-end congestion controls have been proposed to respond to congestion in one round-trip time (RTT). In this paper, we propose a new congestion control mechanism based on backpressure feedback (BFCC), which is designed with the primary goal of switch-to-switch congestion control to resolve congestion in a one-hop RTT. This approach utilizes a programmable data plane to continuously monitor network congestion in real time and identify real-congested flows. In addition, it employs targeted flow control through backpressure feedback. We validate the feasibility of this mechanism on BMV2, a programmable virtual switch based on programming protocol-independent packet processors (P4). Simulation results demonstrate that BFCC greatly enhances flow completion times (FCTs) compared to other end-to-end congestion control mechanisms. It achieves 1.2–2× faster average completion times than other mechanisms.

Suggested Citation

  • Wei Li & Mengzhen Ren & Yazhi Liu & Chenyu Li & Hui Qian & Zhenyou Zhang, 2024. "Congestion Control Mechanism Based on Backpressure Feedback in Data Center Networks," Future Internet, MDPI, vol. 16(4), pages 1-19, April.
    • Handle: RePEc:gam:jftint:v:16:y:2024:i:4:p:131-:d:1375735
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1999-5903/16/4/131/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1999-5903/16/4/131/
    Download Restriction: no
    ---><---

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jftint:v:16:y:2024:i:4:p:131-:d:1375735. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.