TailGate : handling long-tail content with a little help from friends

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Ressource 1Télécharger: Traverso12WWW.pdf (588.96 [Ko])
Etat: Serval
Version: de l'auteur
ID Serval
serval:BIB_8BFE1893AECA
Type
Actes de conférence (partie): contribution originale à la littérature scientifique, publiée à l'occasion de conférences scientifiques, dans un ouvrage de compte-rendu (proceedings), ou dans l'édition spéciale d'un journal reconnu (conference proceedings).
Collection
Publications
Titre
TailGate : handling long-tail content with a little help from friends
Titre de la conférence
Proceedings of the 21st International Conference on the World Wide Web (WWW)
Auteur(s)
Traverso S., Huguenin K., Triestan I., Erramilli V., Laoutaris N., Papagiannaki K.
Editeur
ACM
Adresse
Lyon, France
ISBN
978-1-4503-1229-5
Statut éditorial
Publié
Date de publication
2012
Peer-reviewed
Oui
Pages
151-160
Langue
anglais
Résumé
Distributing long-tail content is an inherently difficult task due to the low amortization of bandwidth transfer costs as such content has limited number of views. Two recent trends are making this problem harder. First, the increasing popularity of user-generated content (UGC) and online social networks (OSNs) create and reinforce such popularity distributions. Second, the recent trend of geo-replicating content across multiple PoPs spread around the world, done for improving quality of experience (QoE) for users and for redundancy reasons, can lead to unnecessary bandwidth costs. We build TailGate, a system that exploits social relationships, regularities in read access patterns, and time-zone differences to efficiently and selectively distribute long-tail content across PoPs. We evaluate TailGate using large traces from an OSN and show that it can decrease WAN bandwidth costs by as much as 80% as well as reduce latency, improving QoE. We deploy TailGate on PlanetLab and show that even in the case when imprecise social information is available, TailGate can still decrease the latency for accessing long-tail YouTube videos by a factor of 2.
Mots-clé
Social networks, Content Distribution, Long-Tail, Geo-Replication
Création de la notice
01/12/2016 11:14
Dernière modification de la notice
03/03/2018 19:12
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