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:arXiv.org 2021-02
Main Authors: Khan, Muhammad, Zaki, Yasir, Iyer, Shiva, Ahamd, Talal, Pötsch, Thomas, Chen, Jay, Sivaraman, Anirudh, Subramanian, Lakshmi
Format: Article
Language:English
Subjects:
Algorithms
Cellular communication
Congestion
Delay
Linear control
Markov chains
Nonlinear analysis
Nonlinear control
Protocol
Protocol (computers)
Random walk
Two dimensional models
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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:2331-8422