A Large-Scale Analysis of Deployed Traffic Differentiation Practices


Northeastern University


David Clark
Net neutrality has been the subject of considerable public debate over the past decade. Despite the potential impact on content providers and users, there is currently a lack of tools or data for stakeholders to independently audit the net neutrality policies of network providers. In this work, we address this issue by conducting a one-year study of content-based traffic differentiation policies deployed in operational networks, using results from 1,045,413 crowdsourced measurements conducted by 126,249 users across 2,735 ISPs in 183 countries/regions. We develop and evaluate a methodology that combines individual per-device measurements to form high-confidence, statistically significant inferences of differentiation practices, including fixed-rate bandwidth limits (i.e., throttling) and delayed throttling practices. Using this approach, we identify differentiation in both cellular and WiFi networks, comprising 30 ISPs in 7 countries. We also investigate the impact of throttling practices on video streaming resolution for several popular video streaming providers.
Fangfan Li is a fourth year computer science PhD student at Northeastern University, advised by David Choffnes. He has a broad interest in understanding the Internet and improving user experience. Recently, he has been working on identifying traffic differentiation practices around the world, understanding how network traffic from different applications are classified, and developing techniques to evade classification. His research products include the Wehe app, which has been installed by more than 100,000 users worldwide, and is currently the official test for identifying net neutrality violations in France (via his team's partnership with the French telecom regulator Arcep).