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.