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Dynamic file bundling for large-scale content distribution

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5 Author(s)
Song Zhang ; Univ. of Calgary, Calgary, AB, Canada ; Carlsson, N. ; Eager, D. ; Zongpeng Li
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One highly-scalable approach to content delivery is to harness the upload bandwidth of the clients. Peer-assisted content delivery systems have been shown to effectively offload the servers of popular files, as the request rates of popular content enable the formation of self-sustaining torrents, where the entire content of the file is available among the peers themselves. However, for less popular files, these systems are less helpful in offloading servers. With a long tail of mildly popular content, with a high aggregate demand, a large fraction of the file requests must still be handled by servers. In this paper, we present the design, implementation, and evaluation of a dynamic file bundling system, where peers are requested to download content which they may not otherwise download in order to “inflate” the popularity of less popular files. Our system introduces the idea of a super bundle, which consists of a large catalogue of files. From this catalogue, smaller bundles, consisting of a small set of files, can dynamically be assigned to individual users. The system can dynamically adjust the number of downloaders of each file and thus enables the popularity inflation to be optimized according to current file popularities and the desired tradeoff between download times and server resource usage. The system is evaluated on PlanetLab.

Published in:

Local Computer Networks (LCN), 2012 IEEE 37th Conference on

Date of Conference:

22-25 Oct. 2012