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Tight Loops, Smooth Streams: Responsive Congestion Control for Real-Time Video

Authors Pantea Karimi , Sadjad Fouladi , Vibhaalakshmi Sivaraman , Mohammad Alizadeh

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OASIcs.NINeS.2026.9.pdf
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ACM Subject Classification
  • Networks → Transport protocols
Keywords
  • real-time video
  • congestion control
  • transport protocols
  • video rate control
  • low-latency video communication
  • tight feedback loop

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Abstract

Real-time video streaming relies on rate control to match video bitrate to network capacity while keeping latency low. Existing deployed video rate controllers react slowly to network changes, causing under-utilization and latency spikes. In contrast, modern delay-sensitive congestion control algorithms (CCAs) adapt on round-trip-time timescales, maintaining a tight feedback loop that achieves both high utilization and low latency. 
We introduce Vidaptive, a lightweight framework that enables real-time video to leverage responsive CCAs without codec changes. Vidaptive decouples encoding from transmission: it paces video frames at the CCA’s rate and injects dummy packets when the encoder output is insufficient, preserving a continuous feedback loop. An online algorithm dynamically adjusts the encoder’s target bitrate to align with CCA capacity while bounding frame latency.
Implemented in Google WebRTC, Vidaptive improves both video quality and tail latency on diverse cellular traces. Compared to GCC, it delivers 1.5× higher bitrate, +40% VMAF, +1.4 dB SSIM, +1.3 dB PSNR, and reduces 95th-percentile frame latency by 57% (2.2 seconds). Against Salsify, it achieves lower tail latency without invasive codec modifications. These results show that coupling existing CCAs with a thin adaptation layer can outperform specialized video rate controllers while remaining deployable in practice.

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Pantea Karimi, Sadjad Fouladi, Vibhaalakshmi Sivaraman, and Mohammad Alizadeh. Tight Loops, Smooth Streams: Responsive Congestion Control for Real-Time Video. In 1st New Ideas in Networked Systems (NINeS 2026). Open Access Series in Informatics (OASIcs), Volume 139, pp. 9:1-9:29, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026) https://doi.org/10.4230/OASIcs.NINeS.2026.9

Author Details

Pantea Karimi
  • Massachusetts Institute of Technology, Cambridge, MA, USA
Sadjad Fouladi
  • Independent Researcher (work performed while at Microsoft Research Redmond), Cambridge, MA, USA
Vibhaalakshmi Sivaraman
  • Amazon (work performed while at MIT), San Francisco, CA, USA
Mohammad Alizadeh
  • Massachusetts Institute of Technology, Cambridge, MA, USA

Acknowledgements

We thank Keith Winstein for countless conversations about this work over the years; this version of the paper would not have been possible without Keith’s insights. We also thank Weiyang "Frank" Wang and Sudarsanan Rajasekaran for their valuable feedback and support. We are grateful to Behnaz Arzani and Siva Kesava Reddy Kakarla for their insightful comments, particularly on framing the narrative of the paper. Finally, we thank our shepherd, Zili Meng, for their guidance throughout the shepherding process.

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