Bursts and heavy tails of execution time in business processes

References

• Amaral, L. A. N., A. Scala, M. Barthélémy, and H. E. Stanley. 2000. “Classes of Small-World Networks.” Proceedings of the National Academy of Sciences 97 (21): 11149–11152.
   PubMed Web of Science ®Google Scholar
• An, L. and J. J. Jeng. 2005. “On Developing System Dynamics Model for Business Process Simulation.” In Proceedings of the 2005 Winter Simulation Conference, 341–346. Orlando, USA.
   Google Scholar
• Barabási, A. L. 2005. “The Origin of Burst and Heavy Tails in Human Dynamics.” Nature 435: 207–211.
   PubMed Web of Science ®Google Scholar
• Bollen, P. 2010. “BPMN: A Meta Model for the Happy Path, Maastricht Research School of Economics of Technology and Organization,” http://edocs.ub.unimaas.nl/ (Accessed November 30, 2011).
   Google Scholar
• Brown, L. D., N. Gans, A. Mandelbaum, A. Sakov, H. Shen, S. Zeltyn, and L. H. Zhao. 2005. “Statistical Analysis of a Telephone Call Center: A Queueing-Science Perspective.” Journal of the American Statistical Association 100: 36–50.
   Web of Science ®Google Scholar
• Budge, S., A. Ingolfsson, and S. Zerom. 2010. “Empirical Analysis of Ambulance Travel Times: The Case of Calgary Emergency Medical Services.” Management Science 56: 716–723.
   Web of Science ®Google Scholar
• Chaintreau, A., P. Hui, J. Crowcroft, C. Diot, R. Gass, and J. Scott. 2007. “Impact of Human Mobility on Opportunistic Forwarding Algorithms.” IEEE Transactions on Mobile Computing 6: 606–620.
   Web of Science ®Google Scholar
• Chen, L. J., Y. C. Chen, T. Sun, P. Sreedevi, K. T. Chen, C. H. Yu, and H. Chu. 2007. “Finding Self-Similarities in Opportunistic People Networks.” 26th IEEE International Conference on Computer Communications Anchorage, AL, 2286–2290.
   Google Scholar
• Drees, H. 2000. “Weighted Approximations of Tail Processes for Mixing Random Variables.” Annals of Applied Probability 10 (4): 1274–1301.
   Web of Science ®Google Scholar
• Duffy, D., A. McIntosh, M. Rosenstein, and W. Willinger. 1994. “Statistical Analysis of CCSN/SS7 Traffic Data from Working CCS Subnetworks.” IEEE Journal of Selected Areas Communications 12: 544–551.
   Web of Science ®Google Scholar
• Gonza´lez, M. C., C. A. Hidalgo, and A. L. Barabási. 2008. “Understanding Individual Human Mobility Patterns.” Nature 453: 779–782.
   PubMed Web of Science ®Google Scholar
• Harchol-Balter, M., M. E. Crovella, and C. D. Murta. 2007. “On Choosing a Task Assignment Policy for a Distributed Server System.” Lecture Notes in Computer Science 1469: 231–242.
   Google Scholar
• Hayakawa, Y. 2000. “The Total Time on Test Statistics and L1-Isotropy.” International Journal of Reliability, Quality and Safety Engineering 7 (2): 143–151.
   Google Scholar
• Hwang, H. C., and B. K. Choi. 2007. “Workflow-Based Dynamic Scheduling of Job Shop Operations.” International Journal of Computer Integrated Manufacturing 20 (6): 557–566.
   Web of Science ®Google Scholar
• Jiang, W., T. Au, and K. L. Tsui. 2007. “A Statistical Process Control Approach to Business Activity Monitoring.” IIE Transactions 39: 235–249.
   Web of Science ®Google Scholar
• Kratz, M., and S. I. Resnick. 1996. “The QQ-Estimator and Heavy Tails.” Stochastic Models 12 (4): 699–724.
   Google Scholar
• Lawson, C. A. 2005. “Business Process Characterization Using Categorical Data Models.” PhD thesis, Arizona State University.
   Google Scholar
• Lee, S. Y. 2001. “Generating Web Workload for Server Performance Evaluation.” Master thesis, Ajou University, Suwon.
   Google Scholar
• Mandelbrot, B. 1983. The Fractal Geometry of Nature. New York, NY: W. H. Freeman.
   Google Scholar
• McNeil, A. 1997. “Estimating the Tails of Loss Severity Distributions Using Extreme Value Theory.” Astin Bulletin 27: 117–137.
   Google Scholar
• Meier-Hellstern, K., P. Wirth, Y. Yan, and D. Hoeflin. 1991. “Traffic Models for ISDN Data Users: Office Automation Application.” In Teletraffic and Datatraffic in a Period of Change, Proceedings of the 13th International Teletraffic Congress, North Holland, Amsterdam, 167–192.
   Google Scholar
• Montgomery, D. C., J. B. Keats, G. C. Runger, and W. S. Messina. 1994. “Integrating Statistical Process Control and Engineering Process Control.” Journal of Quality Technology 26 (2): 79–87.
   Web of Science ®Google Scholar
• Nham, J. 2008. “Size-Independent vs. Size-Dependent Policies in Scheduling Heavy-Tailed Distributions.” Master Thesis, Massachusetts Institute of Technology.
   Google Scholar
• Oliveira, J. G., and A. L. Barabási. 2005. “Human Dynamics: Darwin and Einstein Correspondence Patterns.” Nature 437: 1251.
   PubMed Web of Science ®Google Scholar
• Pinedo, M. 2007. “Stochastic Batch Scheduling and the SMALLEST VARIANCE FIRST Rule.” Probability in the Engineering and Informational Sciences 21: 579–595.
   Web of Science ®Google Scholar
• Rai, I. A., G. Urvoy-Keller, and E. W. Biersack. 2001. “Comparison of PS, SRPT, and FB Scheduling Policies Under Exponential and Heavy Tail Job Sizes.” Technical Report TR-01.11.1, Institut Eurecom, Available from: http://www.eurecom.fr/en/publication/1133 (Accessed February 14, 2013).
   Google Scholar
• Riska, A., E. Smirni, and G. Ciardo. 2000. “Analytic Modeling of Load Balancing Policies for Tasks with Heavy Tailed Distributions.” Proceedings of the 2nd international Workshop on Software and performance. Ottawa, Canada, 147–157.
   Google Scholar
• Russell, N., W. M. P. van der Aalst, and A. H. M. ter Hofstede 2005. “Exception Handling Patterns in Process-Aware Information Systems, Workflow Management Coalition,” Available from: http://www.workflowpatterns.com/patterns/exception (Accessed November 30, 2011).
   Google Scholar
• uEngine: open source BPM project, Available from: http://sourceforge.net/projects/uengine (Accessed January 24, 2013).
   Google Scholar
• Vázquez, A., J. G. Oliveira, Z. Dezsö, K. I. Goh, I. Kondor, and A. L. Barabási. 2006. “Modeling Bursts and Heavy Tails in Human Dynamics.” Physical Review 73 (3): 036127.
   Google Scholar
• Volkner, P., and B. Werners. 2000. “A Decision Support System for Business Process Planning.” European Journal of Operational Research 125: 633–647.
   Web of Science ®Google Scholar
• Whitt, W. 2006. “Sensitivity of Performance in the Erlang A model to Changes in the Model Parameters.” Operations Research 54 (2): 247–260.
   Web of Science ®Google Scholar
• Willinger, W., M. Taqqu, R. Sherman, and D. Wilson. 1997. “Self-Similarity Through High-Variability: Statistical Analysis of Ethernet LAN Traffic at the Source Level.” IEEE/ACM Transactions on Networking 5: 71–96.
   Web of Science ®Google Scholar
• Wohed, P., N. C. Russell, A. H. M. ter Hofstede, B. Andersson, and W. M. P. van der Aalst. 2009. “Patterns-Based Evaluation of Open Source BPM Systems: The Cases of jBPM, OpenWFE, and Enhydra Shark.” Information and Software Technology 51 (8): 1187–1216.
   Google Scholar
• Zakarian, A., P. Wickett, and Y. Siradeghyan. 2006. “Quantitative Model for Evaluating the Quality of an Automotive Business Process.” International Journal of Production Research 44 (6): 1055–1074.
   Google Scholar