RGuide: Fast and Accurate Congestion Control Guided via Explicit Rate Control in Data Center Networks

Congestion control (CC) is crucial in data center networks (DCNs), providing high throughput and low latency transmission services for diverse applications. Existing CC schemes typically rely on iterative rate adjustment at ends, and suffer from performance issues such as slow convergence, throughput fluctuations, and fairness defects. Explicit rate control (ERC) promises to address these challenges by allowing switches to directly allocate rates for each flow, freeing senders from heuristic detection of available bandwidth. However, current ERC-based schemes employ inefficient feedback control to regulate the allocated rates, resulting in sub-optimal performance. In this paper, we propose RGuide, a fast and accurate CC scheme based on ERC. RGuide can calculate accurate fair share rates in real-time at switches with the consideration of low latency, and utilize the rate to guide host adjustments instead of the need for end-to-end iteration processes. We meticulously design the ERC trigger conditions, enabling switches to recognize the different congestion states of flows and rectify flows that deviate from the fair share rate at sub-RTT timescales. We conduct actual testbed experiments and extensive simulations to evaluate RGuide comprehensively. The results demonstrate the significant advantages of RGuide in terms of convergence speed, throughput stability, and fairness.

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Publication Details

Journal
IEEE Transactions on Network and Service Management
Published
2025-06-09
DOI
https://doi.org/10.1109/tnsm.2025.3577951
Citations
1
Primary Topic
Cloud Computing and Resource Management
Type
article
Field-Weighted Citation Impact
3.25

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article

RGuide: Fast and Accurate Congestion Control Guided via Explicit Rate Control in Data Center Networks

Jiangping Han, Jiayu Yang, Jian Li, Wentao Wang et al.
1 citations
IEEE Transactions on Network and Service Management
Cloud Computing and Resource Management
3.25
article

RGuide: Fast and Accurate Congestion Control Guided via Explicit Rate Control in Data Center Networks

Jiangping Han, Jiayu Yang, Jian Li, Wentao Wang, Kaiping Xue, Jun Lu, Qibin Sun
article en
1 citations

Abstract

Congestion control (CC) is crucial in data center networks (DCNs), providing high throughput and low latency transmission services for diverse applications. Existing CC schemes typically rely on iterative rate adjustment at ends, and suffer from performance issues such as slow convergence, throughput fluctuations, and fairness defects. Explicit rate control (ERC) promises to address these challenges by allowing switches to directly allocate rates for each flow, freeing senders from heuristic detection of available bandwidth. However, current ERC-based schemes employ inefficient feedback control to regulate the allocated rates, resulting in sub-optimal performance. In this paper, we propose RGuide, a fast and accurate CC scheme based on ERC. RGuide can calculate accurate fair share rates in real-time at switches with the consideration of low latency, and utilize the rate to guide host adjustments instead of the need for end-to-end iteration processes. We meticulously design the ERC trigger conditions, enabling switches to recognize the different congestion states of flows and rectify flows that deviate from the fair share rate at sub-RTT timescales. We conduct actual testbed experiments and extensive simulations to evaluate RGuide comprehensively. The results demonstrate the significant advantages of RGuide in terms of convergence speed, throughput stability, and fairness.

IEEE Transactions on Network and Service ManagementVol. 22(5)
University of Science and Technology of China (CN), Peng Cheng Laboratory (CN)
National Natural Science Foundation of China, Youth Innovation Promotion Association of the Chinese Academy of Sciences, Fundamental Research Funds for the Central Universities
Openalex Percentile: Top 8%
Cloud Computing and Resource Management
3.25
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