Application Performance Inference on Encrypted Traffic

Video streaming comprises more than 75 percent of today's Internet traffic. Accurately measuring the quality of experience of such service, both in broadband and cellular networks, is paramount. Such measurement helps ISPs detect performance issues, preferably before customers make calls about degraded service. This allows ISPs to take proactive actions that can improve service performance, such as re-routing a stream over a less congested path.

Yet, inferring the quality of an application's service on a network is challenging. This requires both domain expertise in networking, deep understanding of the target application, and systems/DevOps capabilities. Meanwhile, ISPs are spending a massive amount of money on running customer call centers without good answers to provide: not because the lack data but because the lack of an efficient and accurate video QoE monitoring solution.

Network Microscope is 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.


  • Inferring Streaming Video Quality from Encrypted Traffic: Practical Models and Deployment Experience [paper (pdf)]
    F. Bronzino*, P. Schmitt*, S.Ayoubi, G. Martins, R. Teixeira, N. Feamster (*Co-First Authors).
    Proceedings of the ACM on Measurement and Analysis of Computing Systems (POMACS) and at ACM Sigmetrics 2020, Boston, USA, June 8-12, 2020.