Prediction of remaining service execution time using stochastic petri nets with arbitrary firing delays

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 8274 LNCS, Issue , 2013, Pages 389-403

  Rogge Solti, Andreas ^a   Weske, Mathias ^a  

^a UNIVERSITY OF POTSDAM   (Germany)

Author keywords

business process performance; conditional probability; generally distributed durations; remaining time prediction; stochastic Petri nets

Indexed keywords

BUSINESS PROCESS; CONDITIONAL PROBABILITIES; GENERALLY DISTRIBUTED DURATIONS; STOCHASTIC PETRI NETS; TIME PREDICTIONS;

PETRI NETS;

FORECASTING;

EID: 84892422818     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-45005-1_27     Document Type: Conference Paper

References (25)

1. van der Aalst,W.M.P.:Verification of workflow nets. In: Azéma, P., Balbo, G. (eds.) ICATPN 1997. LNCS, vol. 1248, pp. 407-426. Springer, Heidelberg (1997)
2. van der Aalst, W.M.P.: Process Mining: Discovery, Conformance and Enhancement of Business Processes. Springer (2011)
3. van der Aalst, W.M.P., Adriansyah, A., van Dongen, B.F.: Replaying history on process models for conformance checking and performance analysis. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 2, 182-192 (2012)
4. van der Aalst, W.M.P., Schonenberg, M.H., Song, M.: Time prediction based on process mining. Information Systems 36(2), 450-475 (2011)
5. Agrawal, R., Gunopulos, D., Leymann, F.: Mining process models from workflow logs. In: Schek, H.-J., Saltor, F., Ramos, I., Alonso, G. (eds.) EDBT 1998. LNCS, vol. 1377, pp. 469-483. Springer, Heidelberg (1998)
6. Bobbio, A., Telek, M.: Computational restrictions for SPN with generally distributed transition times. In: Echtle, K., Powell, D.R., Hammer, D. (eds.) EDCC 1994. LNCS, vol. 852, pp. 131-148. Springer, Heidelberg (1994)
7. van Dongen, B.F., Crooy, R.A., van der Aalst,W.M.P.: Cycle time prediction:When will this case finally be finished? In:Meersman, R., Tari, Z. (eds.) OTM2008, Part I. LNCS, vol. 5331, pp. 319-336. Springer, Heidelberg (2008)
8. Folino, F., Guarascio, M., Pontieri, L.: Discovering context-aware models for predicting business process performances. In: Meersman, R., et al. (eds.) OTM 2012, Part I. LNCS, vol. 7565, pp. 287-304. Springer, Heidelberg (2012)
9. De Gooijer, J.G., Hyndman, R.J.: 25 years of time series forecasting. International Journal of Forecasting 22(3), 443-473 (2006)
10. Hwang, S.Y., Wang, H., Tang, J., Srivastava, J.: A probabilistic approach to modeling and estimating the QoS of web-services-based workflows. Information Sciences 177(23), 5484-5503 (2007)
11. Härdle, W.: Applied nonparametric regression. Cambridge University Press (1990)
12. Jiang, W., Au, T., Tsui, K.L.: A statistical process control approach to business activity monitoring. IIE Transactions 39(3), 235-249 (2007)
13. Kang, B., Kim, D., Kang, S.H.: Periodic performance prediction for real-time business process monitoring. Industrial Management & Data Systems 112(1), 4-23 (2011)
14. Leitner, P., Wetzstein, B., Rosenberg, F., Michlmayr, A., Dustdar, S., Leymann, F.: Runtime prediction of service level agreement violations for composite services. In: Dan, A., Gittler, F., Toumani, F. (eds.) ICSOC/ServiceWave 2009. LNCS, vol. 6275, pp. 176-186. Springer, Heidelberg (2010)
15. Lohmann, N., Verbeek, E., Dijkman, R.: Petri net transformations for business processes - A survey. In: Jensen, K., van der Aalst, W.M.P. (eds.) ToPNoC II. LNCS, vol. 5460, pp. 46-63. Springer, Heidelberg (2009)
16. Marsan, M.A., Balbo, G., Bobbio, A., Chiola, G., Conte, G., Cumani, A.: The effect of execution policies on the semantics and analysis of stochastic Petri nets. IEEE Transactions on Software Engineering 15(7), 832-846 (1989)
17. Marsan, M.A., Conte, G., Balbo, G.: A class of generalized stochastic Petri nets for the performance evaluation of multiprocessor systems. ACM TOCS 2(2), 93-122 (1984)
18. Pika, A., van der Aalst, W.M.P., Fidge, C.J., ter Hofstede, A.H.M., Wynn, M.T.: Predicting deadline transgressions using event logs. In: La Rosa, M., Soffer, P. (eds.) BPM 2012 Workshops. LNBIP, vol. 132, pp. 211-216. Springer, Heidelberg (2013)
19. Rogge-Solti, A., van der Aalst, W.M.P., Weske, M.: Discovering stochastic Petri nets with arbitrary delay distributions from event logs. In: BPM Workshops. Springer, Heigelberg (to appear)
20. Rozinat, A., Wynn, M.T., van der Aalst, W.M.P., ter Hofstede, A.H.M., Fidge, C.J.: Workflow simulation for operational decision support. Data & Knowledge Engineering 68(9), 834-850 (2009)
21. Strum, D.P., May, J.H., Vargas, L.G.: Modeling the uncertainty of surgical procedure times: Comparison of log-normal and normal models. Anesthesiology 92(4), 1160-1167 (2000)
22. Weske, M.: Business Process Management: Concepts, Languages, Architectures, 2nd edn. Springer (2012)
23. Zeng, L., Lingenfelder, C., Lei, H., Chang, H.: Event-driven quality of service prediction. In: Bouguettaya, A., Krueger, I., Margaria, T. (eds.) ICSOC 2008. LNCS, vol. 5364, pp. 147-161. Springer, Heidelberg (2008)
24. Zheng, H., Yang, J., Zhao, W., Bouguettaya, A.: QoS analysis for web service compositions based on probabilistic QoS. In: Kappel, G., Maamar, Z., Motahari-Nezhad, H.R. (eds.) ICSOC 2011. LNCS, vol. 7084, pp. 47-61. Springer, Heidelberg (2011)
25. Zimmermann, A.: Modeling and evaluation of stochastic Petri nets with TimeNET 4.1. In: 2012 6th International Conference on Performance Evaluation Methodologies and Tools (VALUETOOLS), pp. 54-63. IEEE (2012)