Video QoE Inference

We developed a system that accurately infers video streaming quality metrics in real time, such as startup delay or video resolution, by using just a handful of features extracted from passive traffic measurement. Network Microscope passively collects a corpus of network features about the traffic flows of interest in the network and directs those to a real-time analytics framework that can perform more complex inference tasks. Network Microscope enables network operators to determine degradations in application quality as they happen, even when the traffic is encrypted.

Resources

The research paper was accepted to SIGMETRICS 2020, and published in ACM POMACS in December 2019.

You can download the dataset described in the paper here

Citation bibtex

@article{bronzino2019inferring,
  title={Inferring streaming video quality from encrypted traffic: Practical models and deployment experience},
  author={Bronzino, Francesco and Schmitt, Paul and Ayoubi, Sara and Martins, Guilherme and Teixeira, Renata and Feamster, Nick},
  journal={Proceedings of the ACM on Measurement and Analysis of Computing Systems},
  volume={3},
  number={3},
  pages={1--25},
  year={2019},
  publisher={ACM New York, NY, USA}
}