In this tutorial, we discuss several practical issues regarding specification and solution of dependability and performability models. We compare model types with and without rewards. Continuous-time Markov chains (CTMCs) are compared with (continuous-time) Markov reward models (MRMs) and generalized stochastic Petri nets (GSPNs) are compared with stochastic reward nets (SRNs). It is shown that reward-based models could lead to more concise model specification and solution of a variety of new measures. With respect to the solution of dependability and performability models, we identify three practical issues: largeness, stiffness, and non-exponentiality, and we discuss a variety of approaches to deal with them, including some of the latest research efforts.
Dependability and performability analysis
Abstract
DOI
10.1007/bfb0013869
Year
Biblio Type
Chicago Citation
Trivedi, K. S., G. Ciardo, M. Malhotra, and R. A. Sahner. “Dependability and performability analysis.” In Lecture Notes in Computer Science, 729 LNCS:587–612, 1993. https://doi.org/10.1007/bfb0013869.