Algorithms for High Performance, Wide-area Distributed File Downloads

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

Parallel Processing Letters, Volume 13, Number 2, June, 2003, pages 207-224.

Get the paper from the journal's web site. Who knows how long it will be available without a subscription. If you have problems, send me email and I can send you one of my reprints.

Additionally, you can grab the technical report of the submission.


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.

Citation Information