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System modeling with mixed object and data models
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Source Spring Simulation Multiconference archive
Proceedings of the 2007 spring simulation multiconference - Volume 2 table of contents
Norfolk, Virginia
SESSION: DEVS foundations table of contents
Pages 199-206  
Year of Publication: 2007
ISBN:1-56555-313-6
Authors
Hessam Sarjoughian  IRA Fulton School of Engineering
Robert Flasher  IRA Fulton School of Engineering
Sponsors
SCS : Society for Modeling and Simulation International
ACM/SIGSIM : Association for Computing Machinery/Special Interest Group on Simulation
Publisher
Bibliometrics
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ABSTRACT

System designs are described from object and data centric perspectives. Component-based modeling approaches are well suited to specify structure and behavior of systems in terms of objects and relationships. Ontology-based modeling approaches describe a system's specification using data types and relationships. The Scalable Entity Structure Modeler is a component-based modeling framework suitable for specifying alternative system designs. This approach is extended with XML Schema to support unified dynamic objects and static data specifications for system design specifications. An example illustrating mixed component and data modeling is described using an extended realization of the SESM environment.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
Bendre, S., Behavioral Model Specification Towards Simulation Validation Using Relational Databases, in Computer Science and Engineering, 2004, Arizona State University: Tempe, AZ, p. 1--150.
 
2
Bendre, S. and Sarjoughian, H. S. Discrete-Event Behavioral Modeling in SESM: Software Design and Implementation, Advanced Simulation Technology Symposium, 2005. p. 23--28, San Diego, CA.
 
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Fu, T.-S., Hierarchical Modeling of Large-Scale Systems Using Relational Databases, in Electrical and Computer Engineering, 2002, University of Arizona: Tucson, AZ, p. 1--114.
 
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Mohan, S., Measuring Structural Complexities of Modular, Hierarchical Large-scale Models, in Computer Science and Engineering, 2003, Arizona State University: Tempe, AZ, p. 1--112.
 
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OMG. Unified Modeling Language, 2004, http://www.omg.org/technology/documents/formal/uml.htm
 
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Park, H. C., Lee, W. B., and Kim, T. G., RASES: A Database Supported Framework for Structured Model Base Management, Simulation Practice and Theory, 1997, 5(4), p. 289--313.
 
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Sarjoughian, H. S., An Approach for Scaleable Model Representation and Management, 2001, Computer Science & Engr., Arizona State University: Tempe, AZ, p. 1--9.
 
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Sarjoughian, H. S. A Scaleable Component-based Modeling Environment Supporting Model Validation, Interservice/Industry Training, Simulation, and Education Conference, 2005. p. 1--11 Orlando, FL.
 
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Sarjoughian, H. S., Fu, A., Bendre, S., and Flasher, R., A Unified Logical, Visual, and Persistent Modeling Framework, in-preparation.
 
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SES-Java. Virtual Work Table, http://www.devsworld.org/, 2006.
 
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XML. eXtensible Markup Language, 2005, http://www.w3.org/XML/.
 
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XMLSpy. XML editor for modeling, editing, transforming, & debugging XML technologies, 2006.
 
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Zeigler, B. P. and Hammonds, P. E., Modeling&Simulation-Based Data Engineering: Introducing Pragmatics into Ontologies for Net-Centric Information Exchange, in-press, 2006.
 
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Zeigler, B. P., Praehofer, H., and Kim, T. G., Theory of Modeling and Simulation: Integrating Discrete Event and Continuous Complex Dynamic Systems, Second Edition, 2000: Academic Press.
 
19
Zeigler, B. P. and Zhang, G., The System Entity Structure: Knowledge Representation for Simulation Modeling and Design, in Artificial Intelligence, Simulation and Modeling, K. A. L. L. A. Widman, and N. Nielsen, Editor. 1989, John Wiley. p. 47--73.


Collaborative Colleagues:
Hessam Sarjoughian: colleagues
Robert Flasher: colleagues