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Workflows with transition execution times having exponential distributions are considered. The aim is to determine the overall execution time without looking into the reachability space and its analysis using Markov processes. We concentrate on the so called structural workflows, which are represented with Petri nets constructed by means of specific refinement rules. With each refinement rule (sequence, choice, parallelization, loop) we associate formulas which allow to compute the overall execution time distribution. The class of exponential distributions is too narrow to keep the result within itself. We analyze the so called exponential polynomials, generalizing exponential distributions. They are closed under SUM and MAX functions. This closure property combined with the knowledge of refinements history enables us to find the requested formulas.
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Czasopismo
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Tom
Strony
67--87
Opis fizyczny
bibliogr. 13 poz., wykr.
Twórcy
autor
autor
autor
- Institute of Informatics Warsaw University ul. Banacha 2 02-097 Warsaw, Poland, pch@mimuw.edu.pl
Bibliografia
- [1] van der Aalst,W.: The Application of Petri Nets toWorkflowManagement, The Journal of Circuits, Systems and Computers, 8(1), 1998, 21-66.
- [2] van der Aalst, W., van Hee, K., Reijers, H.: Analysis of Discrete-time Stochastic Petri Nets, Statistica Neerlandica, 54(2), 2000, 237-255.
- [3] Bause, F., Kritzinger, P. S.: Stochastic Petri Nets - An Introduction to the Theory, Vieweg Verlag, Braunschweig/Wiesbaden, 2002.
- [4] Bobbio, A., Trivedi, K. S.: An Aggregation Technique for the Transient Analysis of Stiff Markov Chains, IEEE Trans. on Computers, C-35, 1986, 803-814.
- [5] Chrza¸stowski-Wachtel, P., Benatallah, B., Hamadi, R., O'Dell, M., Susanto, A.: A Top-Down Petri Net-Based Approach for DynamicWorkflow Modeling, BPM 2003, Proceedings, 2678, Springer, 2003.
- [6] Courtois, P. J.: Decomposability: Queueing and Computer System Applications, Academic, New York,1977.
- [7] Haas, P. J.: Stochastic Petri Nets: Modelling, Stability, Simulation, Springer Verlag, New York, 2002.
- [8] Karlin, S.: A First Course in Stochastic Processes, Academic Press, New York, 1966.
- [9] Marie, R. A., Reibman, A. L., Trivedi, K. S.: Transient Analysis of Acyclic Markov Chains, Performance Evaluation, 7, 1987, 175-194.
- [10] Marsan, M. A., Balbo, G., Conte, G., Donatelli, S., Franceschinis, G., Conte, G.: Modelling with Generalized Stochastic Petri Nets, John Wiley & Sons, Inc., New York, NY, USA, 1995.
- [11] Sahner, R. A., Trivedi, K. S.: Performance and reliability analysis using directed acyclic graphs, IEEE Transactions on Software Engineering, SE-13(10), 1987, 1105-1114.
- [12] de Souza e Silva, E., Gail, H. R.: Transient Analysis for Markov Chains, Computational probability, 2000, 43-81.
- [13] Zerguini, L., van Hee, K.: A New ReductionMethod for the Analysis of LargeWorkflowModels, Proceedings of the Joint Annual Conference of the GI Special Interest Groups" Petrinetze und verwandte Systemmodelle" and EMISA (Promise 2002), Potsdam, 2002, 188-201.
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Bibliografia
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bwmeta1.element.baztech-article-BUS5-0016-0005