Research Publications
Dynamic File Bundling for Large-scale Content Distribution 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. Details
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