Unraveling the RTT-fairness Problem for BBR: A Queueing Model
Yuechen Tao, Jingjie Jiang, Shiyao Ma, Luping Wang, Wei Wang, Bo Hu Li · 2018
BBR is a congestion-based congestion control algorithm recently proposed by Google. It proactively measures the bottleneck bandwidth and round trip times (RTTs) of a connection pipe, based on which it governs its sending behaviors. Despite the significant throughput gains and latency reduction, some experimental studies reveal that BBR may result in a salient RTT-fairness problem, in that short-RTT flows can be starved of bandwidth allocation when comnetina with lons-R'I'T flows. In this paper, we study BBR's RTT-fairness problem from a theoretic perspective. We present a closed-form solution that characterizes the intrinsic dynamics of BBR flows and their interactions. Specifically, we model BBR's sending behaviors and bandwidth dynamics, based on which we establish an exponential relationship between the flows' bandwidth shares and their RTTs. We show that the degree of unfairness is dictated by the RTT ratio between two flows, irrespective of the other network parameters, such as the initial sending rates or link capacity. In particular, when the RTT ratio of the two flows is greater than 2, the short-RTT flow is starved of bandwidth allocation ( ≤ 0.1%), Our theoretical results are corroborated by simulations in a wide range of settings.