11th IEEE International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunications Systems (MASCOTS'03) Synthesizing Representative I/O Workloads Using Iterative Distillation Orlando, Florida October 12-October 15 ISBN: 0-7695-2039-1
Storage systems designers are still searching for better methods of obtaining representative I/O workloads to drive studies of I/O systems. Traces of production workloads are very accurate, but inflexible and difficult to obtain. The use of synthetic workloads addresses these limitations; however, synthetic workloads are accurate only if they share certain key properties with the production workload on which they are based (e.g., mean request size, read percentage). Unfortunately, we do not know which properties are "key" for a given workload and storage system.We have developed a tool, the Distiller, that automatically identifies the key properties ("attribute-values") of the workload. The Distiller then uses these attribute-values to generate a synthetic workload representative of the production workload. This paper presents the design and evaluation of the Distiller. We demonstrate how the Distiller finds representative synthetic workloads for simple artificial workloads and three production workload traces.
Citation:
Zachary Kurmas, Kimberly Keeton, Kenneth Mackenzie, "Synthesizing Representative I/O Workloads Using Iterative Distillation," mascots, pp.6, 11th IEEE International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunications Systems (MASCOTS'03), 2003 Usage of this product signifies your acceptance of the Terms of Use. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||