Algorithms for High Performance, Wide-Area, Distributed File Downloads

James S. Plank, Scott Atchley, Ying Ding, and Micah Beck.

Technical Report CS-02-485, University of Tennessee Department of Computer Science, October 8, 2002.

This paper was published in Parallel Processing Letters. See this web page for complete citation information and for details on getting that paper. Please cite that paper in preference to this technical report.

Available via anonymous ftp to in pub/plank/papers/CS-02-485.pdf


This paper explores three algorithms for high-performance downloads of wide-area, replicated data. The storage model is based on the Network Storage Stack, which allows for flexible sharing and utilization of writable storage as a network resource. The algorithms assume that data is replicated in various storage depots in the wide area, and the data must be delivered to the client either as a downloaded file or as a stream to be consumed by an application, such as a media player. The algorithms are threaded and adaptive, attempting to get good performance from nearby replicas, while still utilizing the faraway replicas. After defining the algorithms, we explore their performance downloading a 50 MB file replicated on six storage depots in the U.S., Europe and Asia, to two clients in different parts of the U.S. One algorithm, called progress-driven redundancy exhibits excellent performance characteristics for both file and streaming downloads.

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