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Towards a Dynamic File Bundling System 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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Peer-assisted content delivery systems can provide scalable download service for popular files. For mildly popular content, however, these systems are less helpful in offloading servers as the request rate for less popular files may not enable formation of self-sustaining torrents (where the entire content of the file is available among the peers themselves). As there typically is 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, and is not off-loadable to peers. Bundling approaches have been proposed where peers are requested to download content which they may not otherwise be interested in order to ``inflate'' the popularity of less popular files. We present the design and implementation of a dynamic bundling system, in which a large number of files may be bundled to form a super bundle. From this super bundle, smaller individual bundles, consisting of a small set of files, can dynamically be assigned to individual users. Our system has the capability to dynamically adjust the number of downloaders of each file, thus allowing popularity inflation to be optimized according to current file popularities.

Published in:

Modeling, Analysis & Simulation of Computer and Telecommunication Systems (MASCOTS), 2011 IEEE 19th International Symposium on

Date of Conference:

25-27 July 2011