Synthesizing Representative I/O Workloads Using Iterative Distillation

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 worklo...

• Type: Conference
• Year: 2003
• Where: MASCOTS
• Authors: Zachary Kurmas, Kimberly Keeton, Kenneth Mackenzie
• Keywords: MASCOTS 2003, MASCOTS 2007, Production Workload, Synthetic Workloads, Workload