Queueing networks and Markov processes etc. are widely used in modeling computer systems and communication networks to study their performance and reliability. To solve a real world problem, the model developed has to be validated through measured data. In this paper, we point out that in validating a model, one has to be very clear about one's claims regarding what has been validated; Too "accurate" results do not imply a correct model and usually indicates a validation problem. We discuss some common misconceptions in performance modeling and validation. We illustrate our points through examples. To capture the main concepts, the problems are simplified in these examples.
/lp/association-for-computing-machinery/some-common-misconceptions-about-performance-modeling-and-validation-TrTgPKnIQ4