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Modeling Combined Time-and Event-Driven Dynamic Systems

Real-time distributed systems such as logistical systems, distributed sensor systems and intelligent highway vehicle systems, are complex dynamic systems that not only evolve in real-time but also must respond to unanticipated events. Furthermore, these systems require modeling real-world phenomena accurately as well as solving resource allocation problems for which it is infeasible to find the optimum solution. Modeling such systems requires combining classical methods for analyzing continuous dynamic systems with methods from computer science for analyzing discrete systems. Furthermore, new techniques must be introduced that reconcile these two very different kinds of system, and a new methodology is needed to prove that systems meet requirements other than the classical optimum or reachability properties, such as achieving a solution that is “good enough” as well as “soon enough.” To contribute to this goal, we present an ontology for classifying general systems. This ontology provides a common terminology for understanding different kinds of dynamic system. In addition, we propose an outline of how systems such as real-time distributed resource management systems can be modeled.