Dependability and performability analysis

Abstract

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.

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 Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 729 LNCS:587–612, 1993. https://doi.org/10.1007/bfb0013869.