Four Months in DailyMotion: Dissecting User Video Requests

Yannick Carlinet 1 The Dang Huynh 2, 3 Bruno Kauffmann 1 Fabien Mathieu 2, 4 Ludovic Noirie 2, 3 Sébastien Tixeuil 2, 5, 6
1 Orange Labs [Issy les Moulineaux]
2 LINCS - Laboratory of Information, Network and Communication Sciences
3 Alcatel-Lucent Bell Labs France [Nozay]
4 GANG - Networks, Graphs and Algorithms
LIAFA - Laboratoire d'informatique Algorithmique : Fondements et Applications, Inria Paris-Rocquencourt
5 IUF - Institut Universitaire de France
6 NPA - Networks and Performance Analysis
LIP6 - Laboratoire d'Informatique de Paris 6
Abstract : The growth of User-Generated Content (UGC) traffic makes the understanding of its nature a priority for network operators, content providers and equipment suppliers. In this paper, we study a four-month dataset that logs all video requests to DailyMotion made by a fixed subset of users. We were able to infer user sessions from raw data, to propose a Markovian model of these sessions, and to study video popularity and its evolution over time. The presented results are a first step for synthesizing an artificial (but realistic) traffic that could be used in simulations or experimental testbeds.
Keywords : user-generated content traffic network operators user video requests equipment suppliers daily motion Markovian model
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Yannick Carlinet, The Dang Huynh, Bruno Kauffmann, Fabien Mathieu, Ludovic Noirie, et al.. Four Months in DailyMotion: Dissecting User Video Requests. TRAC 2012 - 3rd International Workshop on TRaffic Analysis and Classification, Aug 2012, Limassol, Cyprus. pp.613-618, ⟨10.1109/IWCMC.2012.6314274⟩. ⟨hal-00692095⟩

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