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This paper presents a case study of modeling, evaluating, and testing the data collection services (called an instrumentation system) of the Paradyn parallel performance measurement tool using well-known performance evaluation and experiment design techniques. The overall objective of the study is to use modeling- and simulation-based evaluation to provide feedback to the tool developers to help them choose system configurations and task scheduling policies that can significantly reduce the data collection overheads. We develop and parameterize a resource occupancy model for the Paradyn instrumentation system (IS) for an IBM SP-2 platform. This model is parameterized with a measurement-based workload characterization and subsequently used to answer several "what if" questions regarding configuration options and two policies to schedule instrumentation system tasks: collect-and-forward (CF) and batch-and-forward (BF) policies. Simulation results indicate that the BF policy can significantly reduce the overheads. Based on this feedback, the BF policy was implemented in the Paradyn IS as an option to manage the data collection. Measurement-based testing results obtained from this enhanced version of the Paradyn IS are reported in this paper and indicate more than 60% reduction in the direct IS overheads when the BF policy is used.