Policing

Large flows like video streams consume significant bandwidth. Some ISPs actively manage these high volume flows with techniques like policing, which enforces a flow rate by dropping excess traffic. While the existence of policing is well known, our contribution is an Internet-wide study quantifying its prevalence and impact on transport level and video-quality metrics. We developed a heuristic to identify policing from server-side traces and built a pipeline to process traces at scale collected from hundreds of Google servers worldwide. Using a dataset of 270 billion packets served to 28,400 client ASes, we find that, depending on region, up to 7% of connections are identified to be policed. Loss rates are on average 6x higher when a trace is policed, and it impacts video playback quality. We show that alternatives to policing, like pacing and shaping, can achieve traffic management goals while avoiding the deleterious effects of policing.

Further Reading

Main Website: https://usc-nsl.github.io/policing-detection/

Tobias Flach, Pavlos Papageorge, Andreas Terzis, Luis Pedrosa, Yuchung Cheng, Tayeb Karim, Ethan Katz-Bassett, and Ramesh Govindan; An Internet-Wide Analysis of Traffic Policing. In Proceedings of the ACM Conference of the Special Interest Group on Data Communication (SIGCOMM'16). 2016
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Tobias Flach, Luis Pedrosa, Ethan Katz-Bassett, and Ramesh Govindan; A Longitudinal Analysis of Traffic Policing Across the Web. Technical Report 15-961, University of Southern California, Computer Science Department. 2015
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Tobias Flach, Pavlos Papageorge, Andreas Terzis, Luis Pedrosa, Ethan Katz-Bassett, and Ramesh Govindan; Stop the Traffic Cop: The Case Against Policing Internet Speed Limits. Best poster at The University of Southern California Computer Science 2015 Annual Research Review. 2015
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Getting the Source

The Policing Detection source code is hosted on the NSL GitHub project website. To create a local copy of the repository run:

git clone https://github.com/USC-NSL/policing-detection.git

People

  • Tobias Flach (USC)
  • Pavlos Papageorge (Google)
  • Andreas Terzis (Google)
  • Luis Pedrosa (USC)
  • Ethan Katz-Bassett (USC)
  • Ramesh Govindan (USC)