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Automated generation and analysis of Markov reward models using stochastic reward nets. (English) Zbl 0799.60085
Meyer, Carl D. (ed.) et al., Linear algebra, Markov chains, and queueing models. Proceedings of the workshop held as part of the year of applied linear algebra at the Institute for Mathematics and its Applications in Minnesota, MN, USA, January 13-17, 1992. New York: Springer-Verlag. IMA Vol. Math. Appl. 48, 145-191 (1993).
The authors propose the use of stochastic reward nets (which are extensions of stochastic Petri nets) for the automatic generation of large Markov reward models, which are widely used in the performance and reliability analysis of computer and communication systems. It contains a review of the solution techniques for the steady state and transient analysis of stochastic reward networks (SRNs) and Markov reward processes and has an extensive list of references. The paper is divided into six sections. The first section is introductory in nature. In Section 2, starting with the definition of Petri nets, the SRN formalism is introduced gradually in steps. Methods of their structural, temporal and sensitivity analysis are discussed in the next two sections. Section 5 is devoted to numerical methods associated with the solutions of equations encountered in SRNs, and the last section closes with brief concluding remarks.
For the entire collection see [Zbl 0779.00020].

MSC:
60K10 Applications of renewal theory (reliability, demand theory, etc.)
90B25 Reliability, availability, maintenance, inspection in operations research
Software:
ESP; SPNP
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