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arXiv · 2102.04911

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

Muhammad Khan·Yasir Zaki·Shiva Iyer·Talal Ahamd·Thomas Pötsch·Jay Chen·Anirudh Sivaraman·Lakshmi Subramanian
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Abstract

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.

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Muhammad Khan, Yasir Zaki, Shiva Iyer, Talal Ahamd, Thomas Pötsch, Jay Chen, Anirudh Sivaraman, Lakshmi Subramanian. 2021-02-09. The case for model-driven interpretability of delay-based congestion control protocols. https://arxiv.org/abs/2102.04911

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