Watching television over an IP network

Abstract

For half a century, television has been a dominant and pervasive mass media, driving many technological advances. Despite its widespread usage and importance to emerging applications, the ingrained TV viewing habits are not completely understood. This was primarily due to the difficulty of instrumenting monitoring devices at individual homes at a large scale. The recent boom of Internet TV (IPTV) has enabled us to monitor the user behavior and network usage of an entire network. Such analysis can provide a clearer picture of how people watch TV and how the underlying networks and systems can better adapt to future challenges. In this paper, we present the first analysis of IPTV workloads based on network traces from one of the world's largest IPTV systems. Our dataset captures the channel change activities of 250,000 households over a six month period. We characterize the properties of viewing sessions, channel popularity dynamics, geographical locality, and channel switching behaviors. We discuss implications of our findings on networks and systems, including the support needed for fast channel changes. Our data analysis of an operational IPTV system has important implications on not only existing and future IPTV systems, but also the design of the open Internet TV distribution systems such as Joost and BBC's iPlayer that distribute television on the wider Internet.

P2P vs. IP multicast: Comparing approaches to IPTV streaming based on TV channel popularity

“…For example, in Fig. 3, Q 2 = 0.4 corresponding to U Á Q 2 /M 2 = 5 viewers per channel, supported by the results from [1] showing that unpopular channels can have as little as 10 viewers. Second, better connected networks, with a higher m, reduce the absolute value of the saved capacity even further.…”

“…The behavior of the users of changing the channels is modeled according to an existing and comprehensive study of users watching TV based on data from a real IPTV service provider [1]. One of the findings from this study is a probability distribution for the channel holding time in a deployed IPTV system, i.e.…”

“…A comprehensive study on watching television [1] revealed that the TV channel popularity is distributed similar to the Pareto principle, the vast majority of channels having only a small fraction of viewers. Depending on the hour of the day, 90% of the channels are watched only by 20% of the total number of active subscribers.…”

The Power of Power Law: A View from VoD Service

“…Gill et al show that the popularity of the YouTube video follows a Zipf-like distribution, where power law is synonymous with Zipf's law [5] . Cha et al show that the popularity of the TV channel in the IP network follows the Zipf-like property, too [6] .…”

“…Gill et al show that the popularity of the YouTube video follows a Zipf-like distribution, where power law is synonymous with Zipf's law [5] . Cha et al show that the popularity of the TV channel in the IP network follows the Zipf-like property, too [6] .When it comes to the link dimensioning, there exists a few literature that deals with the power law. Won et al assume that the popularity of the IPTV program follows a Zipf's law with a binary exponential function where the number of customers for (i-1)-th popular program is twice greater than 608 that of i-th popular program [7] .…”