Meta Introduces a Machine Learning (ML)-based Approach that Allows to Solve Networking Problems Holistically Across Cross-Layers such as BWE

Meta has developed a machine learning (ML)-based approach to improve networking for its apps. The approach aims to solve issues related to bandwidth estimation and congestion control for real-time communication. This will lead to better reliability and quality across different network types, and it will enhance the user experience through congestion prediction and optimization.

Practical Solutions and Value:

– Replacing hand-tuned rules with a simpler alternative for bandwidth estimation and congestion control
– Using time series data for offline parameter tuning and network characterization
– Improving reliability and quality metrics across different network types
– Enhancing user experience through congestion prediction and bandwidth estimation optimization

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