Steady state analysis of markov regenerative SPN with age memory policy
Publication
, Conference
Telek, M; Bobbio, A; Jereb, L; Puliafito, A; Trivedi, KS
Published in: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
January 1, 1995
Non-Markovian Stochastic Petri Nets (SPN) have been developed as a tool to deal with systems characterized by non exponentially distributed timed events. Recently, some effort has been devoted to the study of SPN with generally distributed firing times, whose underlying marking process belongs to the class of Markov Regenerative Processes (MRGP). We refer to this class of models as Markov Regenerative SPN (MRSPN). In this paper, we describe a computationally effective algorithm for the steady state solution of MRSPN with age memory policy and subordinated Continuous Time Markov Chain (CTMC).
Duke Scholars
Published In
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
DOI
EISSN
1611-3349
ISSN
0302-9743
Publication Date
January 1, 1995
Volume
977
Start / End Page
165 / 179
Related Subject Headings
- Artificial Intelligence & Image Processing
- 46 Information and computing sciences
Citation
APA
Chicago
ICMJE
MLA
NLM
Telek, M., Bobbio, A., Jereb, L., Puliafito, A., & Trivedi, K. S. (1995). Steady state analysis of markov regenerative SPN with age memory policy. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 977, pp. 165–179). https://doi.org/10.1007/bfb0024314
Telek, M., A. Bobbio, L. Jereb, A. Puliafito, and K. S. Trivedi. “Steady state analysis of markov regenerative SPN with age memory policy.” In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 977:165–79, 1995. https://doi.org/10.1007/bfb0024314.
Telek M, Bobbio A, Jereb L, Puliafito A, Trivedi KS. Steady state analysis of markov regenerative SPN with age memory policy. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 1995. p. 165–79.
Telek, M., et al. “Steady state analysis of markov regenerative SPN with age memory policy.” Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 977, 1995, pp. 165–79. Scopus, doi:10.1007/bfb0024314.
Telek M, Bobbio A, Jereb L, Puliafito A, Trivedi KS. Steady state analysis of markov regenerative SPN with age memory policy. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 1995. p. 165–179.
Published In
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
DOI
EISSN
1611-3349
ISSN
0302-9743
Publication Date
January 1, 1995
Volume
977
Start / End Page
165 / 179
Related Subject Headings
- Artificial Intelligence & Image Processing
- 46 Information and computing sciences