Access Networks. 5th International ICST Conference on Access Networks, AccessNets 2010 and First ICST International Workshop on Autonomic Networking and Self-Management in Access Networks, SELFMAGICNETS 2010, Budapest, Hungary, November 3-5, 2010, Revised Selected Papers

Research Article

Modeling the Content Popularity Evolution in Video-on-Demand Systems

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  • @INPROCEEDINGS{10.1007/978-3-642-20931-4_4,
        author={Attila Kőr\o{}si and Bal\^{a}zs Sz\^{e}kely and Mikl\^{o}s M\^{a}t\^{e}},
        title={Modeling the Content Popularity Evolution in Video-on-Demand Systems},
        proceedings={Access Networks. 5th International ICST Conference on Access Networks, AccessNets 2010 and First ICST International Workshop on Autonomic Networking and Self-Management in Access Networks, SELFMAGICNETS 2010, Budapest, Hungary, November 3-5, 2010, Revised Selected Papers},
        proceedings_a={ACCESSNETS},
        year={2012},
        month={10},
        keywords={Video popularity analytical model},
        doi={10.1007/978-3-642-20931-4_4}
    }
    
  • Attila Kőrösi
    Balázs Székely
    Miklós Máté
    Year: 2012
    Modeling the Content Popularity Evolution in Video-on-Demand Systems
    ACCESSNETS
    Springer
    DOI: 10.1007/978-3-642-20931-4_4
Attila Kőrösi1,*, Balázs Székely1,*, Miklós Máté1,*
  • 1: Budapest University of Technology and Economics
*Contact email: korosi@tmit.bme.hu, szbalazs@math.bme.hu, mate@tmit.bme.hu

Abstract

The simulation and testing of Video-on-Demand (VoD) services require the generation of realistic content request patterns to emulate a virtual user base. The efficiency of these services depend on the popularity distribution of the video library, thus the traffic generators have to mimic the statistical properties of real life video requests. In this paper the connection among the content popularity descriptors of a generic VoD service is investigated. We provide an analytical model for the relationships among the most important popularity descriptors, such as the ordered long term popularity of the whole video library, the popularity evolutions and the initial popularity of the individual contents. Beyond the theoretical interest, our method provides a simple way of generating realistic request patterns for simulating or testing media servers.