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On the Bottleneck Structure of Congestion-Controlled Networks
06/08/2020Publication Source: ACM SIGMETRICS 2020, Boston MA; Proc. ACM Meas. Anal. Comput. Syst., Vol. 3, No. 3, Article 59, December 2019
In this paper, we introduce the Theory of Bottleneck Ordering, a
mathematical framework that reveals the bottleneck structure of
data networks. This theoretical framework provides insights into
the inherent topological properties of a network at least in three
areas: (1) It identifies the regions of influence of each bottleneck; (2)
it reveals the order in which bottlenecks (and flows traversing them)
converge to their steady state transmission rates in distributed
congestion control algorithms; and (3) it provides key insights to
the design of optimized traffic engineering policies. We demonstrate
the efficacy of the proposed theory in TCP congestion-controlled
networks for two broad classes of algorithms: congestion-based
algorithms (BBR) and loss-based additive-increase/multiplicative-decrease
algorithms (Cubic and Reno). Among other results, our
network experiments show that: (1) Qualitatively, both classes of
congestion control algorithms behave as predicted by the bottleneck
structure of the network; (2) flows compete for bandwidth only
with other flows operating at the same bottleneck level; (3) BBR
flows achieve higher performance and fairness than Cubic and Reno
flows due to their ability to operate at the right bottleneck level;
(4) the bottleneck structure of a network is ever-changing and its
levels can be folded due to variations in the flows’ round trip times;
and (5) against conventional wisdom, low-hitter flows can have a
large impact to the overall performance of a network.
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