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In software engineering, performance and the integration of performance analysis methodologies gain increasing importance, especially for complex systems. Well-developed methods and tools can predict non-functional performance properties like response time or resource utilization in early design stages, thus promising time and cost savings. However, as performance modeling and performance prediction is still a young research area, the methods are not yet well-established and in wide-spread industrial use. The authors model and analyze different design alternatives for storage virtualization on an IBM system. The model calibration, validation and evaluation is based on data measured on a System z9 as a proof of concept.
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