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Dissecting User Behaviors for a Simultaneous Live and VoD IPTV System

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Published:17 April 2014Publication History
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Abstract

IPTV services deployed nowadays often consist of both live TV and Video-on-Demand (VoD), offered by the same service provider to the same pool of users over the same managed network. Understanding user behaviors in such a setting is hence an important step for system modelling and optimization. Previous studies on user behavior on video services were on either live TV or VoD. For the first time, we conduct an in-depth large-scale behavior study for IPTV users offering simultaneously live TV and VoD choices at the same time. Our data is from the largest IPTV service provider in China, offering hundreds of live channels and hundreds of thousands of VoD files, with traces covering more than 1.9 million users over a period of 5 months. This large dataset provides us a unique opportunity to cross-compare user viewing behaviors for these services on the same platform, and sheds valuable insights on how users interact with such a simultaneous system.

Our results lead to new understanding on IPTV user behaviors which have strong implications on system design. For example, we find that the average holding time for VoD is significantly longer than live TV. live TV users tend to surf more. However, if such channel surfing is discounted, the holding times of both services are not much different. While users in VoD tend to view HD longer, channel popularity for live TV is much less dependent on its video quality. In contrast to some popular assumptions on user interactivity, the transitions among live TV, VoD, and offline modes are far from a Markov model.

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      • Published in

        cover image ACM Transactions on Multimedia Computing, Communications, and Applications
        ACM Transactions on Multimedia Computing, Communications, and Applications  Volume 10, Issue 3
        April 2014
        140 pages
        ISSN:1551-6857
        EISSN:1551-6865
        DOI:10.1145/2602979
        Issue’s Table of Contents

        Copyright © 2014 ACM

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        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 17 April 2014
        • Accepted: 1 February 2014
        • Revised: 1 December 2013
        • Received: 1 September 2013
        Published in tomm Volume 10, Issue 3

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