The case for model-driven interpretability of delay-based congestion control protocols
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.
Cite
@article{arxiv.2102.04911,
title = {The case for model-driven interpretability of delay-based congestion control protocols},
author = {Muhammad Khan and Yasir Zaki and Shiva Iyer and Talal Ahamd and Thomas Pötsch and Jay Chen and Anirudh Sivaraman and Lakshmi Subramanian},
journal= {arXiv preprint arXiv:2102.04911},
year = {2021}
}