An Internet-Wide Analysis of Traffic Policing
Abstract
Large flows like videos 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 video quality metrics.
We developed a heuristic to identify policing from
server-side traces and built a pipeline to deploy it at scale on
hundreds of servers worldwide within one of the largest online
content providers. Using a dataset of 270 billion packets
served to 28,400 client ASes, we find that, depending on region,
up to 7% of lossy transfers are policed. Loss rates are
on average 6× 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.
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 video quality metrics.
We developed a heuristic to identify policing from
server-side traces and built a pipeline to deploy it at scale on
hundreds of servers worldwide within one of the largest online
content providers. Using a dataset of 270 billion packets
served to 28,400 client ASes, we find that, depending on region,
up to 7% of lossy transfers are policed. Loss rates are
on average 6× 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.
Research Areas
