The case for model-driven interpretability of delay-based congestion control protocols

Analyzing and interpreting the exact behavior of new delay-based congestion control protocols with complex non-linear control loops is exceptionally difficult in highly variable networks such as cellular networks. This paper proposes a Model-Driven Interpretability (MDI) congestion control framework...

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Bibliographic Details
Published in:Computer communication review 2021-01, Vol.51 (1), p.18-25
Main Authors: Khan, Muhammad, Zaki, Yasir, Iyer, Shiva, Ahamd, Talal, Poetsch, Thomas, Chen, Jay, Sivaraman, Anirudh, Subramanian, Lakshmi
Format: Magazinearticle
Language:English
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Summary:Analyzing and interpreting the exact behavior of new delay-based congestion control protocols with complex non-linear control loops is exceptionally difficult in highly variable networks such as cellular networks. This paper proposes a Model-Driven Interpretability (MDI) congestion control framework, which derives a model version of a delay-based protocol by simplifying a congestion control protocol's response into a guided random walk over a two-dimensional Markov model. We demonstrate the case for the MDI framework by using MDI to analyze and interpret the behavior of two delay-based protocols over cellular channels: Verus and Copa. Our results show a successful approximation of throughput and delay characteristics of the protocols' model versions across variable network conditions. The learned model of a protocol provides key insights into an algorithm's convergence properties.
ISSN:0146-4833
DOI:10.1145/3457175.3457179