TY - GEN
T1 - Performance characterization of a commercial video streaming service
AU - Ghasemi, Mojgan
AU - Kanuparthy, Partha
AU - Mansy, Ahmed
AU - Benson, Theophilus
AU - Rexford, Jennifer
N1 - Funding Information:
This work was in part supported by the National Science Foundation grant CNS-1162112.
PY - 2016/11/14
Y1 - 2016/11/14
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85000819103&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85000819103&partnerID=8YFLogxK
U2 - 10.1145/2987443.2987481
DO - 10.1145/2987443.2987481
M3 - Conference contribution
AN - SCOPUS:85000819103
T3 - Proceedings of the ACM SIGCOMM Internet Measurement Conference, IMC
SP - 499
EP - 511
BT - IMC 2016 - Proceedings of the 2016 ACM Internet Measurement Conference
PB - Association for Computing Machinery
T2 - 2016 ACM Internet Measurement Conference, IMC 2016
Y2 - 14 November 2016 through 16 November 2016
ER -