Empirical validation of availability models for the RISC System/6000 workstation using survey and measurement data

Abstract

We show an empirically driven process to validate the availability models of RISC System/6000 workstations. The empirical data is obtained by tracking RISC System/6000 workstations in the field. The tracking data is obtained by using customer surveys and by using an availability measurement tool installed on selected running systems. We model several types of RISC System/6000 workstations using the SAVE tool. Care is taken to include all classes of systems. The workstations modeled include representatives from the desktop, deskside, and rack families. We explain the key principle of the "representative field model." For each type of workstation modeled, availability data for validation is extracted from the customer survey database or the availability measurement database. The validation data is used to identify and eliminate model errors. The identification and elimination of modeling errors involves sensitivity analysis. The validation of the availability measures of several RISC System/6000 workstations using both survey and measurement data confirms the accuracy of our modeling process and gives us the confidence to utilize the availability models in our development and marketing processes. Also, this enables us to generate accurate availability measures in our future availability modeling efforts.