Discrete Event Formalisms and Simulation Model Development
The theory and techniques of discrete event modelling and simulation have advanced substantially over the past two decades. An integrative approach, making use of discrete event formalisms, should now be used when developing computer simulations. An important formalism is the DEVS model — a mathematical representation of the class of discrete event systems. Other formalisms, such as modelling strategies, provide a “world view” in which to conceptualize the simulation model.
In this chapter, the formalisms are first described. Next, detailed case studies of simulations within three problem domains are considered: (1) insect population dynamics; (2) nuclear waste management; and (3) computer communication networks. For each case study, the formalisms are shown as intimately intertwined in the model formulation and simulation development.
KeywordsPermeability Migration Covariance Shale Drilling
Unable to display preview. Download preview PDF.
- Aggarwal, S., S. Ryland and R. Peck, (1981). “Discrete Event Simulation of Nuclear Waste Transport in Geologic Sites Subject to Disruptive Events,”Dept. of Mathematics Tech. Report., Univ. of California, Riverside.Google Scholar
- Aggarwal, S., (1982). “Flexibility of Computer Network Simulation Using the Hierarchical Class Concept,” 10th IMACS Proceedings, Montreal.Google Scholar
- Hooper, J. W., and K. D. Reilly, (1981). “Analyzing Simulation Strategies,” Preprint, University of Alabama in Birmingham.Google Scholar
- Kreutzer, W., (1976). “Comparison and Evaluation of Discrete Event Simulation Programming Languages for Management Decision Making,” 8th AICA Congress 76 on Simulation and Systems, North-Holland.Google Scholar
- Metcalf, R. M., and D. R. Boggs, (1976). “Ethernet: Distributed Packet Switching for Local Computer Networks,” CACM, Vol. 19, No. 7. Google Scholar
- Oddson, J. K., and S. Aggarwal, “A Discrete Event Model of Navel Orangeworm on Almonds,” (forthcoming).Google Scholar
- Patten, B. C., (ed.), (1971–75). Systems Analysis and Simulation in Ecology, Vols. 1–4, Academic Press.Google Scholar
- Peck, R., and S. Aggarwal, (1979). “Discrete Events Modelling of Post-emplacement Risks Associated with Nuclear Waste Disposal,” 1979 Summer Computer Simulation Conference, Toronto.Google Scholar
- Scheidegger, A. E., (1961). “General Theory of Dispersion in Porous Media,” J. Geophy. Res., Vol. 66. Google Scholar
- Shoch, J. F. and J. A. Hupp, (1979). “Measured Performance of an Ethernet Local Network,”Local Area Communications Symposium, Boston.Google Scholar
- Stroustrup, B., (1980). “A Set of C Classes for Co-routine Style Programming,” Computing Sci. Tech. Report 90, Bell Labs.Google Scholar
- Stroustrup, B., (1982). “Classes: An Abstract Data Type Facility for the C Language,” ACM Sigplan Notices, Vol. 17, No. 1. Google Scholar
- Tanenbaum, A. S., (1981). Computer Networks, Prentice-Hall.Google Scholar
- Zeigler, B. P., (1976). Theory of Modelling and Simulation, J. Wiley and Sons, New York.Google Scholar
- Zeigler, B. P., (1977). “Persistence and Patchiness of Predator-Prey Systems Induced by Discrete Event Population Exchange Mechanisms,” Journal of Theoretical Biology, 67.Google Scholar
- Zeigler, B. P., et al. (eds.), (1979). Methodology in Systems Modelling and Simulation, North–Holland.Google Scholar