Results 191 to 200 of about 60,348 (227)

Markov regenerative stochastic Petri nets

Performance Evaluation, 1994
Abstract Stochastic Petri nets of various types (SPN, GSPN, ESPN, DSPN etc.) are recognized as useful modeling tools for analyzing the performance and reliability of systems. The analysis of such Petri nets proceeds by utilizing the underlying continuous-time stochastic processes — continuous-time Markov chains for SPN and GSPN, semi-Markov processes
Kishor S. Trivedi, Vidyadhar G. Kulkarni, Hoon Choi   +2 more
openaire   +2 more sources

Evaluating High Availability-Aware Deployments Using Stochastic Petri Net Model and Cloud Scoring Selection Tool

IEEE Transactions on Services Computing, 2021
Manar Jammal, A. Kanso, P. Heidari, Aballah Shami   +3 more
semanticscholar   +1 more source

Arbitrary Stochastic Petri Nets

1998
Recall Section 5.1.3. When the firing policy for an STPN is the race with enabling age memory (R-E), the marginal distributions in (5.5) are the residual life distributions of t k conditioned to age variable a k :
openaire   +2 more sources

Colored Stochastic Petri Nets

2002
Use of the standard set of SPN building blocks to model very large or complex systems can sometimes result in nets that have an enormous number of places and transitions. One popular strategy for obtaining more concise specifications in such cases is to associate “colors” with both tokens and transitions and to work with “colored stochastic Petri nets”
openaire   +2 more sources

The fluid stochastic Petri net simulator

Proceedings 6th International Workshop on Petri Nets and Performance Models, 2002
A Fluid Stochastic Petri Net (FSPN) extends a normal Petri net with the notion of fluid places, and fluid arcs. Fluid levels are continuous, and may be used to approximate the presence of many discrete tokens. We describe an FSPN simulation tool whose input description extends the syntax of the widely used tool spnp.
David M. Nicol, Andrew S. Miner
openaire   +2 more sources

Modelling with Stochastic Petri Nets

2002
Stochastic Petri nets (SPNs) are well suited to representing concurrency, synchronization, precedence, and priority. After presenting the basic SPN building blocks in Section 2.1, we give a series of examples in Section 2.2 that illustrates the use of SPNs for modelling discrete-event systems.
openaire   +2 more sources

Analysis of deterministic and stochastic Petri nets

Proceedings of 5th International Workshop on Petri Nets and Performance Models, 2002
A time and space efficient algorithm for computing steady state solutions of deterministic and stochastic Petri nets (DSPNs) with both stochastic and structural extensions is presented. The algorithm can deal with different execution policies associated with deterministic transitions of a DSPN.
Gianfranco Ciardo, Christoph Lindemann
openaire   +2 more sources

Generalized Stochastic Petri Nets

1998
The key factor that limits the applicability of SPN models is the complexity of their analysis. This is due to many elements. The possibly very large number of reachable markings is the most critical one. Other aspects may add to the model solution complexity.
openaire   +2 more sources

Modelling a remanufacturing reverse logistics system using fuzzy stochastic Petri net

, 2015
This paper defines the concept of fuzzy stochastic Petri net (FSPN) based on Petri net theory and credibility theory and proposes an approach for modelling and analysis of reverse logistics using FSPN in both stochastic and fuzzy environments.
Junyan Wang, Xiaozhong Li, Guoli Wang, Ziping Du   +3 more
semanticscholar   +1 more source

Risk assessment of FPSO topside based on generalized Stochastic Petri Net

, 2021
Jichuan Kang, Xin Geng, Xu Bai, Yan Dong
semanticscholar   +1 more source