Exploiting Heterogeneity for Collective Data Downloading in Volunteer-based Networks

13 years 10 months ago

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Abstract— Scientiﬁc computing is being increasingly deployed over volunteer-based distributed computing environments consisting of idle resources on donated user machines. A fundamental challenge in these environments is the dissemination of data to the computation nodes, with the successful completion of jobs being driven by the efﬁciency of collective data download across compute nodes, and not only the individual download times. This paper considers the use of a data network consisting of data distributed across a set of data servers, and focuses on the server selection problem: how do individual nodes select a server for downloading data to minimize the communication makespan—the maximal download time for a data ﬁle. Through experiments conducted on a Pastry network running on PlanetLab, we demonstrate that nodes in a volunteer-based network are heterogeneous in terms of several metrics, such as bandwidth, load, and capacity, which impact their download behavior. We propo...

Jinoh Kim, Abhishek Chandra, Jon B. Weissman

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