Standard Quantitative Evaluation Methods for SDES

Different modeling formalisms and their translation into a general SDES model have been covered in the previous chapters. One of the main reasons for constructing an SDES model is the prediction of properties of the modeled system. This chapter describes a selection of well‐known analysis methods that derive quantitative measures from the model, and which can thus be used for a performance and dependability evaluation of a planned system. The starting point is always the dynamic behavior of a model over time, which is given by the stochastic process described by the model as shown in Sect. 2.3.2, and the derivation of the reward measures of interest.

Examples of measures include performance (often in terms of throughput), dependability issues, and combinations of them. They are expressed by reward variables in an SDES model as it has been described in Sect. 2.4.1. The applications described in Part III include different examples. A model‐based experiment requires a model, performance measures, and their type (e.g., transient or steady‐state). The selection of an evaluation algorithm depends on the type of reward variable as well as the mathematical complexity of the solution, because preferable algorithms might exist for models with certain restrictions.