Campus Event Calendar

Event Entry

What and Who

"Trace-driven analysis of streaming services: A deep look into YouTube and a nationwide IPTV"

Meeyoung Cha
SWS Colloquium

Meeyoung Cha is a PhD candidate in Computer Science at KAIST, Korea.  Her advisor is Dr. Sue Moon.  She is working on
the network design and support for multimedia streaming services.  Previously, she was an intern at AT&T Labs
Research in NJ, where she participated in the cost comparison of IPTV backbone designs.  Recently, she was an intern at
Telefonica Research in Barcelona, Spain, and in University of Cambridge, UK, where she analyzed a nationwide IPTV system
and the world's largest VoD for user-generated contents, YouTube.   She also maintains interests in path diversity
issues in intra- and inter-domain routing.  She expects to graduate in Feb 2008.
AG 1, AG 2, AG 3, AG 4, AG 5, SWS, RG1, RG2  
Expert Audience

Date, Time and Location

Thursday, 13 December 2007
60 Minutes
E1 5


Multimedia streaming is becoming an integral part of people's life.  In this talk, I will present data analysis on
user's viewing behaviors based on two streaming services: YouTube and IPTV.  YouTube is the largest VoD service for user
generated contents (UGC).  Nowadays, UGC sites are creating new viewing patterns and social interactions, empowering
users to be more creative, and developing new business opportunities.  In this talk, I will present the intrinsic
statistical properties of video popularity based on real traces from YouTube. Understanding the popularity
characteristics is important because it can bring forward the latent demand created by bottlenecks in the system (e.g.
poor search and recommendation engines, lack of metadata, etc).

Another popular form of streaming is IPTV.  After many years of academic and industry work, we are finally witnessing a
thriving of IP multicast in large scale deployment of IPTV services.  In the second part of this talk, I will present
for the first time previously hidden TV viewing habits based on real traces.  I will also discuss the feasibility of
using peer-to-peer distribution for scalable IPTV system and supporting advanced viewing controls such as DVD-like
functionalities, content recommendations, and target advertisements.


Brigitta Hansen
0681 - 9325200
--email hidden
passcode not visible
logged in users only

Brigitta Hansen, 12/11/2007 11:27 -- Created document.