Name
Abstract | ||
|---|---|---|
M.D. Beaudry (1978) proposed a simple method of computing the distribution of performability in a Markov reward process. Two extensions of Beaudry's approach are presented. The authors generalize the method to a semi-Markov reward process by removing the restriction requiring the association of zero reward to absorbing states only. The algorithm proceeds by replacing zero reward nonabsorbing states by a probabilistic switch; it is therefore related to the elimination of vanishing states from the reachability graph of a generalized stochastic Petri net and to the elimination of fast transient states in a decomposition approach to stiff Markov chains. The use of the approach is illustrated with three applications. |
Year | DOI | Venue |
|---|---|---|
1990 | 10.1109/12.59855 | Computers, IEEE Transactions |
Keywords | Field | DocType |
Markov processes,performance evaluation,decomposition,fast transient states elimination,performability analysis,probabilistic switch,reachability graph,semi-Markov reward processes,stiff Markov chains,stochastic Petri net,vanishing states elimination,zero reward nonabsorbing states | Markov process,Markov model,Computer science,Parallel computing,Markov chain,Reachability,Real-time computing,Multiprocessing,Stochastic Petri net,Probabilistic logic,Application software | Journal |
Volume | Issue | ISSN |
39 | 10 | 0018-9340 |
Citations | PageRank | References |
42 | 8.68 | 10 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Gianfranco Ciardo | 1 | 2144 | 178.59 |
| R. A. Marie | 2 | 103 | 13.94 |
| B. Sericola | 3 | 71 | 12.47 |
| K. S. Trivedi | 4 | 136 | 21.48 |