  Google's BBR is the most prominent result of the recently revived quest for
efficient, fair, and flexible congestion-control algorithms (CCAs). While the
performance of BBR has been investigated by numerous studies, previous work
still leaves gaps in the understanding of BBR performance: Experiment-based
studies generally only consider network settings that researchers can set up
with manageable effort, and model-based studies neglect important issues like
convergence.
  To complement previous BBR analyses, this paper presents a fluid model of
BBRv1 and BBRv2, allowing both efficient simulation under a wide variety of
network settings and analytical treatment such as stability analysis. By
experimental validation, we show that our fluid model provides highly accurate
predictions of BBR behavior. Through extensive simulations and theoretical
analysis, we arrive at several insights into both BBR versions, including a
previously unknown bufferbloat issue in BBRv2.

Networking and Internet Architecture