ABSTRACT
A modeling process is a method by which people understand a concerned object, system, or phenomenon. Various modeling methods, tools, and models have been developed since people started to design man-made and engineering systems to benefit human beings. It is well known that mathematical modeling helps one to understand, analyze, evaluate, simulate, and control the systems under consideration. Traditionally, a resulting mathematical model is a description of a system in terms of equations. These equations are derived based on physical laws, such as Newton’s laws, using continuous variables driven by time. Discrete time models are driven by clocks such that values of a variable at discrete times are observed, studied, analyzed, and used. The last type of models are discrete event driven. In other words, they represent the evolution of system states as driven by events that are often asynchronous. This asynchrony distinguishes the last class of models from the other two types. As a result, differential or difference equations cannot be used to describe them. We have to seek new models in order to well describe asynchronous event-driven dynamics. Additional features include concurrency, choices, and mutually exclusive use of shared resources. In reality, hybrid models may be used to describe the components/subsystems, interactions among components/subsystems, and the entire system.
