Performance Characterization of a Commercial Video Streaming Service

TL;DR

This study provides a comprehensive analysis of Yahoo's video streaming service, identifying key performance issues and their causes through large-scale data collection and instrumentation at both server and client levels.

Contribution

It offers the first detailed end-to-end characterization of a commercial video streaming service, revealing persistent performance problems and their dependencies.

Findings

Identified server-side cache misses and disk-read delays as performance bottlenecks.

Discovered network latency and variability significantly impact user experience.

Observed client-side buffering delays and dropped frames affecting video quality.

Abstract

Despite the growing popularity of video streaming over the Internet, problems such as re-buffering and high startup latency continue to plague users. In this paper, we present an end-to-end characterization of Yahoo's video streaming service, analyzing over 500 million video chunks downloaded over a two-week period. We gain unique visibility into the causes of performance degradation by instrumenting both the CDN server and the client player at the chunk level, while also collecting frequent snapshots of TCP variables from the server network stack. We uncover a range of performance issues, including an asynchronous disk-read timer and cache misses at the server, high latency and latency variability in the network, and buffering delays and dropped frames at the client. Looking across chunks in the same session, or destined to the same IP prefix, we see how some performance problems are relatively persistent, depending on the video's popularity, the distance between the client and server, and the client's operating system, browser, and Flash runtime.