Fork: A Dual Congestion Control Loop for Small and Large Flows in Datacenters

Many existing transport designs aim to deliver ultra-low latency and high bandwidth for applications in high-speed datacenter networks. However, almost all of them intertwine the control of small and large flows using the same control entity (e.g., sender or receiver) and congestion feedback signal (e.g., ECN or credit), thus bringing significant performance impairments. By contrast, we seek to decouple the rate control of small flows from that of large ones.

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Publication Details

Published
2025-03-26
DOI
https://doi.org/10.1145/3689031.3696101
Citations
2
Primary Topic
Cloud Computing and Resource Management
Type
article
Field-Weighted Citation Impact
6.49
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article

Fork: A Dual Congestion Control Loop for Small and Large Flows in Datacenters

G. M. Liu, Xin Nan Xie, Wenyu Qu, Xiao-Mei Gao et al.
2 citations
Cloud Computing and Resource Management
6.49
article

Fork: A Dual Congestion Control Loop for Small and Large Flows in Datacenters

G. M. Liu, Xin Nan Xie, Wenyu Qu, Xiao-Mei Gao, Lide Suo, Ziqi Fan, Sheng Chen, Yuan Liu, Wenxin Li, Yulong Li
article en
2 citations

Abstract

Many existing transport designs aim to deliver ultra-low latency and high bandwidth for applications in high-speed datacenter networks. However, almost all of them intertwine the control of small and large flows using the same control entity (e.g., sender or receiver) and congestion feedback signal (e.g., ECN or credit), thus bringing significant performance impairments. By contrast, we seek to decouple the rate control of small flows from that of large ones.

Tianjin University of Technology (CN), Tianjin University (CN), Peking University (CN)
Openalex Percentile: Top 4%
Cloud Computing and Resource Management
6.49
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