Kangsun Lee
Abstract
When we build a model of real-time systems, we need ways of representing the knowledge about the system and also time requirements for simulating the model. Considering these different needs, our question is “How can we determine the optimal model that simulates the system by a given deadline while still producing valid outputs at an acceptable level of detail?” We have designed OOPM/RT (Object-Oriented Physical Modeler for Real-Time Simulation) methodology. The OOPM/RT framework has three phases: (1) Generation of multimodels in OOPM using both structural and behavioral abstraction techniques, (2) Generation of AT (Abstraction Tree) which organizes the multimodels based on the abstraction relationship to facilitate the optimal model selection process, and (3) Selection of the optimal model that guarantees the deliver simulation results by the given amount of time. A more-detailed model (low abstraction model) is selected when we have enough time to simulate, while a less-detailed model (high abstraction model) is selected when the deadline is immediate. The basic idea of selection is to trade structural information for a faster runtime while minimizing the loss of behavioral information. We propose two possible approaches for the selection: an integer-programming-based approach and a search-based approach. By systematically handling simulation deadlines while minimizing the modeler's interventions, OOPM/RT provides an efficient modeling environment for real-time systems.
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Index Terms
- OOPM/RT: a multimodeling methodology for real-time simulation
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Reviews
David H. Withers
This well-written paper describes a method for automatically selecting the best levels of abstraction and detail for forming a simulation model that will execute within a constrained time horizon while meeting a prescribed accuracy. The motivation for the research was simulation of real-time systems. The authors argue that current software engineering tools cannot ensure the performance of a new or revised system, though other requirement specifications can be confirmed as present in the design by appropriate representation tools and methods. They argue that the performance of the system usually cannot be determined until development is complete. The research centers on an object-oriented approach to simulation. This approach allows an optimization algorithm to be used to select the method (abstraction or decomposition) for each node in a hierarchical decomposition of the model of the proposed system. A simple example is included, namely, a continuous model of a dynamic system. I believe that the methodology could be applied for any system where performance is of interest, not just real-time systems. I did not realize that the application is targeted for continuous models until I read the example. This point could have been made earlier to enhance readability.
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