DEDS Stochastic Behaviour and Modelling

  • Louis G. Birta
  • Gilbert Arbez
Part of the Simulation Foundations, Methods and Applications book series (SFMA)


This chapter is devoted to the modelling and simulation process within the domain of discrete-event dynamic systems (DEDS). This chapter provides a foundation for these discussions by exploring a variety of key topics. To a large extent the discussion is dominated by considerations relating to the inherently stochastic nature of the DEDS domain. Within this context we introduce the notion of a discrete-time variable which is central to our characterization of both the input and output of a conceptual model. Related concepts such as random number generation, random variate generation, random variate procedures and deterministic value procedures are also introduced. The need to recognize an important distinction between two general categories of modelling and simulation studies is emphasized. This relates to the nature of the observation interval that is associated with the study and two associated notions are pointed out, namely, bounded horizon studies and steady-state studies. Data modelling is likewise an important facet of model development in the DEDS domain, and important aspects of this topic are discussed.


Cumulative Distribution Function Busy Period Observation Interval Theoretical Distribution Exogenous Input 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag London 2013

Authors and Affiliations

  • Louis G. Birta
    • 1
  • Gilbert Arbez
    • 1
  1. 1.School of Electrical Engineering and Computer ScienceUniversity of OttawaOttawaCanada

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