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Andrea Bobbio, Antonio Puliafito, Miklós Telek, "A Modeling Framework to Implement Preemption Policies in NonMarkovian SPNs," IEEE Transactions on Software Engineering, vol. 26, no. 1, pp. 3654, January, 2000.  
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@article{ 10.1109/32.825765, author = {Andrea Bobbio and Antonio Puliafito and Miklós Telek}, title = {A Modeling Framework to Implement Preemption Policies in NonMarkovian SPNs}, journal ={IEEE Transactions on Software Engineering}, volume = {26}, number = {1}, issn = {00985589}, year = {2000}, pages = {3654}, doi = {http://doi.ieeecomputersociety.org/10.1109/32.825765}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }  
RefWorks Procite/RefMan/Endnote  x  
TY  JOUR JO  IEEE Transactions on Software Engineering TI  A Modeling Framework to Implement Preemption Policies in NonMarkovian SPNs IS  1 SN  00985589 SP36 EP54 EPD  3654 A1  Andrea Bobbio, A1  Antonio Puliafito, A1  Miklós Telek, PY  2000 KW  Stochastic Petri Nets KW  Markov regenerative processes KW  preemptive policies KW  transient and steadystate analysis. VL  26 JA  IEEE Transactions on Software Engineering ER   
Abstract—Petri nets represent a useful tool for performance, dependability, and performability analysis of complex systems. Their modeling power can be increased even more if nonexponentially distributed events are considered. However, the inclusion of nonexponential distributions destroys the memoryless property and requires to specify how the marking process is conditioned upon its past history. In this paper, we consider, in particular, the class of stochastic Petri nets whose marking process can be mapped into a Markov regenerative process. An adequate mathematical framework is developed to deal with the considered class of Markov Regenerative Stochastic Petri Nets (
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