This paper demonstrates the use of a model-based evaluation approach for instrumentation systems (ISs). The overall objective of this study is to provide early feedback to tool developers regarding IS overhead and performance; such feedback helps developers make appropriate design decisions about alternative system configurations and task scheduling policies. We consider three types of system architectures: network of workstations (NOW), symmetric multiprocessors (SMP), and massively parallel processing (MPP) systems. We develop a Resource OCCupancy (ROCC) model for an on-line IS for an existing tool and parameterize it for an IBM SP-2 platform. This model is simulated to answer several ?what if? questions regarding two policies to schedule instrumentation data forwarding: collect-and-forward (CF) and batch-and-forward (BF). In addition, this study investigates two alternatives for forwarding the instrumentation data: direct and binary tree forwarding for an MPP system. Simulation results indicate that the BF policy can significantly reduce the overhead and that the tree forwarding configuration exhibits desirable scalability characteristics for MPP systems. Initial measurement-based testing results indicate more than 60 percent reduction in the direct IS overhead when the BF policy was added to Paradyn parallel performance measurement tool