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

Researchers from Meta developed a machine learning (ML)-based approach to address the challenges of optimizing bandwidth estimation (BWE) and congestion control for real-time communication (RTC) across Meta’s family of apps. Existing techniques, such as WebRTC’s Google Congestion Controller (GCC), rely on hand-tuned parameters, leading to complexities and inefficiencies in handling diverse network conditions. Maintaining a […]

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

ai shorts applications apps artificial intelligence bandwidth challenges communication congestion control editors pick family gcc google machine machine learning meta networking real-time real-time communication researchers solve staff tech news technology