TailGate: Handling Long-Tail Content with a Little Help from Friends

Abstract : 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 decreaseWAN 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.
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Stefano Traverso, Kévin Huguenin, Ionut Trestian, Vijay Erramilli, Nikolaos Laoutaris, et al.. TailGate: Handling Long-Tail Content with a Little Help from Friends. 21st International Conference on the World Wide Web (WWW), Apr 2012, Lyon, France. pp.151-160, ⟨10.1145/2187836.2187858⟩. ⟨hal-00665868⟩

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