Popularity prediction in content delivery networks

Abstract : —Content delivery networks (CDNs) face a large and continuously increasing number of users solicitations for video contents. In this paper, we focus on the prediction of popularity evolution of video contents. Based on the observation of past solicitations of individual video contents, individual future solici-tations are predicted. We compare different prediction strategies: SES, DES and Basic. The best tuning of each strategy is determined, depending on the considered phase of the solicitation curve. Since DES and Basic experts outperform the SES expert, our method combines DES and Basic experts to predict the number of solicitations within a phase and automatically detect the phase changes, respectively. This self-learning and prediction method can be applied to optimize resources allocation in service oriented architectures and self-adaptive networks, more precisely for the CDN cache nodes management.
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Communication dans un congrès
IEEE 26th Annual International Symposium on Personal, Indoor and Mobile radio Communications (PIMRC), Aug 2015, Hong Kong, China. 2015, 〈10.1109/PIMRC.2015.7343641〉
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https://hal.inria.fr/hal-01244908
Contributeur : Nesrine Ben Hassine <>
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Dernière modification le : vendredi 25 mai 2018 - 12:02:07
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Nesrine Ben Hassine, Dana Marinca, Pascale Minet, Dominique Barth. Popularity prediction in content delivery networks. IEEE 26th Annual International Symposium on Personal, Indoor and Mobile radio Communications (PIMRC), Aug 2015, Hong Kong, China. 2015, 〈10.1109/PIMRC.2015.7343641〉. 〈hal-01244908〉

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