Fairness of Congestion-Based Congestion Control: Experimental Evaluation and Analysis
Shiyao Ma, Jingjie Jiang, Wei Wang, Bo Li

TL;DR
This paper investigates the RTT fairness issues in BBR congestion control, revealing that longer RTT flows dominate shorter ones due to probing behavior, and proposes a modified BBR to ensure fairness without sacrificing performance.
Contribution
The paper provides a thorough measurement, theoretical analysis, and a modified BBR algorithm that guarantees flow fairness while maintaining BBR's advantages.
Findings
RTT disparities cause bandwidth unfairness in BBR.
Longer RTT flows can dominate shorter ones, even causing starvation.
A modified BBR achieves fairness without performance loss.
Abstract
BBR is a new congestion-based congestion control algorithm proposed by Google. A BBR flow sequentially measures the bottleneck bandwidth and round-trip delay of the network pipe, and uses the measured results to govern its sending behavior, maximizing the delivery bandwidth while minimizing the delay. However, our deployment in geo-distributed cloud servers reveals a severe RTT fairness problem: a BBR flow with longer RTT dominates a competing flow with shorter RTT. Somewhat surprisingly, our deployment of BBR on the Internet and an in-house cluster unearthed a consistent bandwidth disparity among competing flows. Long BBR flows are bound to seize bandwidth from short ones. Intrigued by this unexpected behavior, we ask, is the phenomenon intrinsic to BBR? how's the severity? and what's the root cause? To this end, we conduct thorough measurements and develop a theoretical model on…
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Taxonomy
TopicsNetwork Traffic and Congestion Control · Peer-to-Peer Network Technologies · Software-Defined Networks and 5G
