A Control-Theoretic Perspective on BBR/CUBIC Congestion-Control Competition

TL;DR

This paper uses control theory to analyze the fairness and instability issues in BBR and CUBIC congestion control algorithms, providing conditions for oscillation and fairness bounds, and suggesting remedies.

Contribution

It extends a dynamic fluid model of BBR with control theory to predict oscillation conditions and fairness impacts in BBR/CUBIC competition.

Findings

BBR/CUBIC oscillation is frequent in practical networks.

Oscillation harms BBR fairness and can be predicted with the model.

Control-theoretic analysis suggests potential remedies for instability.

Abstract

To understand the fairness properties of the BBR congestion-control algorithm (CCA), previous research has analyzed BBR behavior with a variety of models. However, previous model-based work suffers from a trade-off between accuracy and interpretability: While dynamic fluid models generate highly accurate predictions through simulation, the causes of their predictions cannot be easily understood. In contrast, steady-state models predict CCA behavior in a manner that is intuitively understandable, but often less accurate. This trade-off is especially consequential when analyzing the competition between BBR and traditional loss-based CCAs, as this competition often suffers from instability, i.e., sending-rate oscillation. Steady-state models cannot predict this instability at all, and fluid-model simulation cannot yield analytical results regarding preconditions and severity of the oscillation. To overcome this trade-off, we extend the recent dynamic fluid model of BBR by means of control theory. Based on this control-theoretic analysis, we derive quantitative conditions for BBR/CUBIC oscillation, identify network settings that are susceptible to instability, and find that these conditions are frequently satisfied by practical networks. Our analysis illuminates the fairness implications of BBR/CUBIC oscillation, namely by deriving and experimentally validating fairness bounds that reflect the extreme rate distributions during oscillation. In summary, our analysis shows that BBR/CUBIC oscillation is frequent and harms BBR fairness, but can be remedied by means of our control-theoretic framework.