ANALYTICAL PERFORMANCE MODELING OF HIERARCHICAL MASS-STORAGE SYSTEMS

Mass storage systems are finding greater use in scientific computing r esearch environments for retrieving and archiving the large volumes of data generated and manipulated by scientific computations. This paper presents a queuing network model that can be used to carry out capaci ty planning studies of hierarchical mass storage systems. Measurements taken on a Unitree mass storage system and a detailed workload charac terization provided the workload intensity and resource demand paramet ers for the various types of read and write requests. The performance model developed here is based on approximations to multiclass Mean Val ue Analysis of queuing networks. The approximations were validated thr ough the use of discrete event simulation and the complete model was v alidated and calibrated through measurements. The resulting model was used to analyze three different scenarios: effect of workload intensit y increase, use of file compression at the server and client, and use of file abstractions.