End-to-end Performance Management for Scalable Distributed Storage

Abstract

Many applications—for example, scientific simulation, real-time data acquisition, and distributed reservation systems—have I/O performance requirements, yet most large, distributed storage systems lack the ability to guarantee I/O performance. We are working on end-to-end performance management in scalable, distributed storage systems. The kinds of storage systems we are targeting include large high-performance computing (HPC) clusters, which require both large data volumes and high I/O rates, as well as large-scale general-purpose storage systems.

Publication
Proceedings of the 2007 ACM Petascale Data Storage Workshop (PDSW 07)

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