Galdino, SĂ©rgio; Maciel, Paulo; Rosa, Nelson S. Interval Markovian models in dependability evaluation. (English) Zbl 1135.93030 Int. J. Pure Appl. Math. 41, No. 2, 151-176 (2007). Summary: Model-based dependability evaluation is based on abstractions of the real system. When uncertainties or variabilities are associated with system parameters, single point characterization of parameters is inadequate. Interval arithmetic has been applied to model uncertainties and variabilities. An interval model is a space, family or class of models in which there are parameters represented by intervals, instead of real numbers. This paper describes the Interval Generalized Stochastic Petri Net (IGSPN) as an interval extension to the GSPN model. The IGSPN analysis takes into account the effects of variability on exponential transition rates and weights when calculating dependability measures. IGSPN analysis may be useful as a tool for decision-making. A case study related to availability evaluation of two network devices widely used in communication networks, namely a multiplexer ADM and a multiplexer SDH. MSC: 93E03 Stochastic systems in control theory (general) 93A30 Mathematical modelling of systems (MSC2010) 93C41 Control/observation systems with incomplete information 93C65 Discrete event control/observation systems 65G30 Interval and finite arithmetic 60J27 Continuous-time Markov processes on discrete state spaces Keywords:interval models; stochastic modeling; dependability measures; stochastic Petri nets Software:INTLAB PDFBibTeX XMLCite \textit{S. Galdino} et al., Int. J. Pure Appl. Math. 41, No. 2, 151--176 (2007; Zbl 1135.93030)