Numerical transient analysis of Markov models
Computers and Operations Research
Fast and simple decomposition techniques for the reliability analysis of interconnection networks
Journal of Systems and Software
R-nets for the performance evaluation of hard real-time systems
Journal of Systems and Software
A probabilistic dynamic technique for the distributed generation of very large state spaces
Performance Evaluation - Special issue on modelling techniques and tools for performance evaluation
Accurate approximate analysis of cell-based switch architectures
Performance Evaluation
Performance Evaluation of Client-Server Systems
IEEE Transactions on Parallel and Distributed Systems
Petri Nets for System Engineering: A Guide to Modeling, Verification, and Applications
Petri Nets for System Engineering: A Guide to Modeling, Verification, and Applications
DrawNET++: Model Objects to Support Performance Analysis and Simulation of Systems
TOOLS '02 Proceedings of the 12th International Conference on Computer Performance Evaluation, Modelling Techniques and Tools
Symbolic Methods for the State Space Exploration of GSPN Models
TOOLS '02 Proceedings of the 12th International Conference on Computer Performance Evaluation, Modelling Techniques and Tools
Efficient State Space Generation of GSPNs using Decision Diagrams
DSN '02 Proceedings of the 2002 International Conference on Dependable Systems and Networks
Moses - a tool suite for visual modeling of discrete-event systems
HCC '01 Proceedings of the IEEE 2001 Symposia on Human Centric Computing Languages and Environments (HCC'01)
Performance Analysis of the CORBA Event Service Using Stochastic Reward Nets
SRDS '00 Proceedings of the 19th IEEE Symposium on Reliable Distributed Systems
Parametric stochastic well-formed nets and compositional modelling
ICATPN'00 Proceedings of the 21st international conference on Application and theory of petri nets
Modeling a flexible manufacturing cell using stochastic Petri nets with fuzzy parameters
Expert Systems with Applications: An International Journal
Modelization of a communication protocol for CSCW systems using coloured petri nets
CDVE'05 Proceedings of the Second international conference on Cooperative Design, Visualization, and Engineering
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An interesting modeling problem is the need to model one or more of the system modules without exposition to the other system modules. This modeling problem arises due to our interest in these modules or incomplete knowledge, or inherent complexity, of the rest of the system modules. Whenever the performance measures (one or more) of the desired modules are available through previous performance studies, data sheets, or previous experimental works, the required performance measures for the whole system can be predicted from our proposed modeling technique. The incomplete knowledge problem of the dynamic behavior of some system modules has been studied by control theory. In the control area, such systems are known as partially observed discrete event dynamic systems, or POS systems. To the best of our knowledge, the performance evaluation of the POS system has not been addressed by the Petri net theory yet. Therefore, in this paper, we propose a new modeling technique for solving this kind of problem based on using the Petri net theory (i.e. Stochastic Reward Nets (SRNs)) in conjunction with the optimal control theory. In this technique, we develop an SRN Equivalent Model (EM) for the modeled system. The SRN EM-model consists of two main nets and their interface nets. One of the main nets represents the part(s) of interest or the known part(s) of the overall POS system that allows us to model its dynamic behavior and evaluate its performance measures. The other main net represents the remaining part(s) of the overall POS system that feeds the part(s) of interest. The well-known maximum principles have been used to develop an algorithm for determining the unknown transition rates of the proposed model. Numerical simulations are given to show that the proposed approach is more effective than the conventional modeling techniques, especially when dealing with systems having a large number of states.