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On the Bottleneck Structure of Congestion-Controlled Networks

Proceedings of the ACM on Measurement and Analysis of Computing Systems2019Vol. 3(3), pp. 1–31

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Jordi Ros-Giralt, Atul Bohara, Sruthi Yellamraju, M. Harper Langston, Richard Lethin, Yuang Jiang, Leandros Tassiulas, Josie Li, Yuanlong Tan, Malathi Veeraraghavan

Abstract

In this paper, we introduce theTheory 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 in at least 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 into 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 (TCP BBR) and loss-based additive-increase/multiplicative-decrease algorithms (TCP 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 continuously 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.

Citations Over TimeTop 15% of 2019 papers

Abstract

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