Cited By
View all- Shim HFishwick P(2005)Programming using dynamic system modeling VIA a 3D-based multimodeling frameworkProceedings of the 37th conference on Winter simulation10.5555/1162708.1163043(1931-1938)Online publication date: 4-Dec-2005
Next generation modeling I: RUBE: a customized 2d and 3d modeling framework for simulation
Abstract
We present a system called RUBE, which allows a modeler to customize model components and model structure in 2D and 3D. RUBE employs open source tools to assist in model authoring, allowing the user to visualize models with different metaphors. For example, it is possible to visualize an event graph as a city block, or a Petri network as an organically-oriented 3D machine. We suggest that such flexibility in visualization will allow existing model types to take on forms that may be more recognizable to modeling subcommunities, while employing notation as afforded by inexpensive graphical hardware. There is also a possibility to create model types using entirely new notations.
References
[1]
J. T. Buck, Ha S., E. A. Lee, and D. G. Messerschmitt. 1994. Ptolemy: A Framework for Simulating and Prototyping Heterogeneous Systems, Int. Journal of Computer Simulation, special issue on Simulation Software Development, 4:155--182.
[2]
H. Elmqvist, S. E. Mattsson, and M. Otter. 1999. Modelica - A Language for Physical System Modeling, Visualization and Interaction, Plenary paper. IEEE Symposium on Computer-Aided Control System Design, CACSD'99, 630--639. Hawaii.
[3]
P. A. Fishwick and B. P. Zeigler. 1992. A Multimodel Methodology for Qualitative Model Engineering, ACM Transactions on Modeling and Computer Simulation, 2(1):52--81.
[4]
P. A. Fishwick. 1995. Simulation Model Design and Execution: Building Digital Worlds. Englewood Cliffs, NJ: Prentice-Hall. P. A. Fishwick. 1996. Web-Based Simulation: Some Personal Observations, Proceedings of the 1996 Winter Simulation Conference, 772--779. San Diego, CA.
[5]
P. A. Fishwick. 2002. rube: An XML-Based Architecture for 3D Process Modeling and Model Fusion, Proceedings of Enabling Technology for Simulation Science, Part of SPIE Aerosense '02 Conference, 330--335. Orlando, FL.
[6]
T. Kim and P. A. Fishwick. 2002. An XML-Based Visualization and Simulation Framework for Dynamic Models. Proceedings of Enabling Technology for Simulation Science, Part of SPIE Aerosense '02 Conference, 336--347. Orlando, FL.
[7]
T. G. Kirner and V. F. Martins. 2000. Development of an Information Visualization Tool Using Virtual Reality. Proceedings of the 2000 ACM symposium on Applied computing, 604--606.
[8]
E. A. Lee and S. Neuendorffer. 2000. MoML - A Modeling Markup Language in XML, Version 0.4, Technical Memorandum UCB/ERL M00/12, University of California, Berkeley, CA 94720.
[9]
J. Lee and P. A. Fishwick. 2002. A Dynamic Exchange Language Layer for rube, Proceedings of Enabling Technology for Simulation Science, Part of SPIE Aerosense '02 Conference, 359--366. Orlando, FL.
[10]
X. Liu, J. Liu, J. Eker, and E. Lee. 2002. Heterogeneous Modeling and Design of Control Systems, to appear in Software-Enabled Control: Information Technology for Dynamic Systems, New York, IEEE Press.
[11]
S. E. Mattsson, H. Elmqvist, and M. Otter. 1998. Physical System Modeling with Modelica, Control Engineering Practice 6:501--510,.
[12]
R. E. Nance 1996. A History of Discrete Event Simulation Programming Languages, In History of Programming Languages, ACM Press and Addison-Wesley Publishing Co., 369--427.
[13]
R. E. Nance, E. M. Overstreet, and E. H. Page. 1999. Redundancy in Model Specification for Discrete Event Simulation. ACM Transactions on Modeling and Computer Simulation 9(3):254--281.
[14]
A. Orso, J. Jones, and M. J. Harrold. 2003. Visualization of Program-Execution Eata for Deployed Software. Proceedings of the 2003 ACM symposium on Software visualization, 67--76.
[15]
E. H. Page, P. A. Fishwick, K. J. Healy, R. E. Nance, and R. J. Paul. 1998. The Modeling Methodological Impacts of Web-Based Simulation. Proceedings of the 1998 International Conference on Web-Based Modeling & Simulation, Simulation Series, Volume 30, Number 1, P. A. Fishwick, D. R. C. Hill, and R. Smith, Eds. Society for Computer Simulation, 123--130. San Diego, CA.
[16]
E. H. Page, A. Buss, P. A. Fishwick, K. J. Healy, R. E. Nance, and R. J. Paul. 2000. Web-Based Simulations: Revolution or Evolution? ACM Transactions on Modeling and Computer Simulation, 10(1):3--17.
[17]
M. Park and P. A. Fishwick. 2002. SimPackJ/S: A Web-Oriented Toolkit for Discrete Event Simulation, Proceedings of Enabling Technology for Simulation Science, Part of SPIE Aerosense '02 Conference, 348--358. Orlando, FL.
[18]
M. Tiller. 2001. Introduction to Physical System Modeling with Modelica. Kluwer International Series in Engineering and Computer Science, 615, Kluwer Publishing.
[19]
B. P. Zeigler. 1984. Multifacetted Modeling and Discrete Event Simulation, Academic Press.
[20]
B. P. Zeigler, H. Praehofer, and T. G. Kim. 2001. Theory of Modleing and Simulation: Integrating Discrete Event and Continuous Complex Dynamic Systems, Second Edition, Academic Press.
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- IIE: Institute of Industrial Engineers
- INFORMS/CS: Institute for Operations Research and the Management Sciences/College on Simulation
- ASA: American Statistical Association
- ACM: Association for Computing Machinery
- SIGSIM: ACM Special Interest Group on Simulation and Modeling
- IEEE/CS: Institute of Electrical and Electronics Engineers/Computer Society
- NIST: National Institute of Standards and Technology
- (SCS): The Society for Modeling and Simulation International
- IEEE/SMCS: Institute of Electrical and Electronics Engineers/Systems, Man, and Cybernetics Society
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Winter Simulation Conference
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Published: 07 December 2003
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WSC '03 Paper Acceptance Rate 128 of 189 submissions, 68%;
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Cited By
View all- Shim HFishwick P(2005)Programming using dynamic system modeling VIA a 3D-based multimodeling frameworkProceedings of the 37th conference on Winter simulation10.5555/1162708.1163043(1931-1938)Online publication date: 4-Dec-2005
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