Understanding User Behavior in Large-Scale Video-on-Demand Systems
Ben Y. Zhao
1st EuroSys (EuroSys 2006)
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Video-on-demand over IP (VOD) is one of the best-known examples of
"next-generation" Internet applications cited as a goal by networking and
multimedia researchers. Without empirical data, researchers have generally
relied on simulated models to drive their design and developmental efforts.
In this paper, we
present one of the first measurement studies of a large VOD system, using
data covering 219 days and more than 150,000 users in a VOD system deployed by
China Telecom. Our study focuses on user behavior, content access patterns,
and their implications on the design of multimedia streaming systems.
Our results also show that when used to model the user-arrival rate, the
traditional Poisson model is conservative and overestimates the probability
of large arrival groups. We introduce a modified Poisson distribution that
more accurately models our observations. We also observe a surprising
result, that video session lengths have a weak inverse correlation with
video popularity. Finally, we gain better understanding of
the sources of video popularity through analysis of a number of internal
and external factors.