Scalable Enterprise Systems: Discrete Event System Specification (DEVS) as a Formal Modeling Framework for Scaleable Enterprise Design - Case Study: Model-Driven Data Management

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This research will investigate a theoretical foundation for a major responsibility of enterprise systems to ensure that the right information about the enterprise is available to decision makers at the right time. The Internet and e-commerce are rapidly creating an environment in which businesses can be usefully likened to organisms which must tap into the relevant features of their environments to make rapid life/death decisions-where even what is relevant is continually in flux. The primary focus of this project is to formulate an approach to incorporating flexibility in connecting decision-makers (brain) to dynamically relevant data sources (internal and external environment) to support time-critical decisions. Within this framework, the research will study the application of model-driven data acquisition, filtering and attention mechanisms to achieve flexible sensor-to-decision maker connectivity.Enterprise resource planning (ERP) systems are a response to the realization that manufacturing control systems cannot function in isolation from other major enterprise functions. The objectives of ERP systems should also include standardization of principal functional modules to minimize customization and enhance reusability. The ultimate result of this research would be a framework for scalable enterprise system development that does not constrain the continued development of the framework as would a pure software code-based approach. Based on a mathematical formalism, the modules developed would not be bound to any one technology but would be amenable to transition to scalable network infrastructures as they evolve. The development of a model-based framework for goal-driven data delivery could ultimately guide the design of scalable data management as well as other standardized modules in flexible corporate enterprise systems.