2012 Poster Sessions : Understanding Rate-Adaptation Algorithm in HTTP-based Video on Demand Streaming Service

Student Name : Te-Yuan Huang
Advisor : Ramesh Johari
Research Areas: Information Systems
The market of video on demand (VoD) has been growing over the past few years. People enjoy having control over which video to watch and the timeliness of delivery that VoD service provides. In 2011, Sandvine reported that Netflix, the biggest VoD service provider in the United States, accounted for 30% of all US Internet traffic. As video traffic becomes a dominant part of Internet traffic, every design decision would be magnified and will have a huge impact on the Internet. In this poster, I will focus on understanding the rate-adaptation algorithm in an HTTP-based VoD streaming service and its interaction with other traffic on the Internet.

Te-Yuan Huang is a Ph.D. candidate in Computer Science, Stanford University.
Her research focuses on rethinking the client-side network stack design to better support multimedia traffic. Te-Yuan received her M.S. in Electrical Engineering from National Taiwan University in 2008 and B.S. in Computer Science from National Chiao-Tung University in 2006.