Events Driven Approach for Supporting Real-Time Management of Complex Systems

Management and modeling of complex systems is a challenging area of research. One of the approaches to modeling such systems is event driven modeling and management of a complex system. The application of the concept of event to systems modeling has been applied for modeling of discrete systems, of stochastic systems, etc. However, most of the existing modeling approaches use only information about the type of event and the time when an event occurs. Contemporary information systems store much richer information about events, in both structured and unstructured forms. Structured information is stored in databases in the form of tables. Unstructured information is stored in various forms of textual or even visual information. Both types of information should be considered and used to analyze and predict events in more advanced events driven modeling approaches. Figure 1 shows the basic components of an event driven modeling framework: the system that is influenced by external and internal events, data and textual information about the system and about events, models, algorithms, event detection algorithms, knowledge representation, description of decision maker behavior and actions. In order to build models or algorithms we have to store the data about the system and the events.