Discrete Event Formalisms and Simulation Model Development

  • Sudhir Aggarwal
Part of the NATO ASI Series book series (volume 10)

Abstract

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.

Keywords

Permeability Migration Covariance Shale Drilling 

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References

  1. 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
  2. Aggarwal, S., (1982). “Flexibility of Computer Network Simulation Using the Hierarchical Class Concept,” 10th IMACS Proceedings, Montreal.Google Scholar
  3. Bear, J., (1972). Dynamics of Fluids in Porous Media, American Elsevier, New York.MATHGoogle Scholar
  4. Fishman, G. S., (1978). Principles of Discrete Event Simulation, Wiley and Sons, New York.MATHGoogle Scholar
  5. Franta, W. R., (1977). The Process View of Simulation, North-Holland.MATHGoogle Scholar
  6. Freedman, H. I., (1980). Deterministic Mathematical Models in Population Ecology, Marcel Dekker, Inc.MATHGoogle Scholar
  7. Hooper, J. W., and K. D. Reilly, (1981). “Analyzing Simulation Strategies,” Preprint, University of Alabama in Birmingham.Google Scholar
  8. 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
  9. Metcalf, R. M., and D. R. Boggs, (1976). “Ethernet: Distributed Packet Switching for Local Computer Networks,” CACM, Vol. 19, No. 7. Google Scholar
  10. Oddson, J. K., and S. Aggarwal, “A Discrete Event Model of Navel Orangeworm on Almonds,” (forthcoming).Google Scholar
  11. Oren, T. I., and B. P. Zeigler, (1979). “Concepts for Advanced Simulation Methodologies,” Simulation, 32,3. CrossRefGoogle Scholar
  12. Padulo, L., and M. A. Arbib, (1974). System Theory, Saunders.MATHGoogle Scholar
  13. Patten, B. C., (ed.), (1971–75). Systems Analysis and Simulation in Ecology, Vols. 1–4, Academic Press.Google Scholar
  14. 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
  15. Scheidegger, A. E., (1961). “General Theory of Dispersion in Porous Media,” J. Geophy. Res., Vol. 66. Google Scholar
  16. Shoch, J. F. and J. A. Hupp, (1979). “Measured Performance of an Ethernet Local Network,”Local Area Communications Symposium, Boston.Google Scholar
  17. Stroustrup, B., (1980). “A Set of C Classes for Co-routine Style Programming,” Computing Sci. Tech. Report 90, Bell Labs.Google Scholar
  18. Stroustrup, B., (1982). “Classes: An Abstract Data Type Facility for the C Language,” ACM Sigplan Notices, Vol. 17, No. 1. Google Scholar
  19. Tanenbaum, A. S., (1981). Computer Networks, Prentice-Hall.Google Scholar
  20. Zeigler, B. P., (1976). Theory of Modelling and Simulation, J. Wiley and Sons, New York.Google Scholar
  21. 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
  22. Zeigler, B. P., et al. (eds.), (1979). Methodology in Systems Modelling and Simulation, North–Holland.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1984

Authors and Affiliations

  • Sudhir Aggarwal
    • 1
    • 2
  1. 1.Department of MathematicsUniversity of California, RiversideRiversideUSA
  2. 2.Bell LaboratoriesMurray HillUSA

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