Abstract
Abstract: Realistic computer systems are hard to model using state-based methods because of the large state spaces they require and the likely stiffness of the resulting models (because activities occur at many time scales). One way to address this problem is to decompose a model into submodels, which are solved separately but exchange results. We call modeling formalisms that support such techniques "connection formalisms." In this paper, we describe a new set of connection formalisms that reduce state-space size and solution time by identifying submodels that are not affected by the rest of a model, and solving them separately. A result from each solved submodel is then used in the solution of the rest of the model. We demonstrate the use of two of these connection formalisms by modeling a real-world file server in the M?bius modeling framework. The connected models were solved one to two orders of magnitude faster than the original model, with one of these decomposition techniques introducing an error of less than 11%.