Modeling communication software execution for accurate simulation of distributed systems

Network simulation is commonly used to evaluate the performance of distributed systems, but these approaches do not account for the performance impact that protocol execution on nodes has on performance, which may be significant. We propose a methodology to capture execution models from communication software running on real devices where the execution models can be integrated with discrete event network simulators to improve their accuracy. We provide a set of rules to instrument the software to obtain the events of importance, and present techniques to create executable models based on the obtained traces. To make the models scalable, processing stages are reduced to statistical distributions. When the resulting models are executed in a device model with a scheduler simulator, we are able to model the dynamics of multithreading and parallel execution. Our initial results from a proof-of-concept extension to Ns-3 show that our models are able to accurately model protocol execution on the Google Nexus One with low simulation overhead.