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Front. Inform. Technol. Electron. Eng.  2014, Vol. 15 Issue (1): 1-12    DOI: 10.1631/jzus.C1300089
    
Quantitative evaluation of model consistency evolution in compositional service-oriented simulation using a connected hyper-digraph
Lin-jun Fan, Yun-xiang Ling, Xing-tao Zhang, Jun Tang
Science and Technology on Information Systems Engineering Laboratory, National University of Defense Technology, Changsha 410073, China; Department of Telecommunications and Systems Engineering, Universitat Autónoma de Barcelona, Barcelona 08202, Spain
Quantitative evaluation of model consistency evolution in compositional service-oriented simulation using a connected hyper-digraph
Lin-jun Fan, Yun-xiang Ling, Xing-tao Zhang, Jun Tang
Science and Technology on Information Systems Engineering Laboratory, National University of Defense Technology, Changsha 410073, China; Department of Telecommunications and Systems Engineering, Universitat Autónoma de Barcelona, Barcelona 08202, Spain
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摘要： Appropriate maintenance technologies that facilitate model consistency in distributed simulation systems are relevant but generally unavailable. To resolve this problem, we analyze the main factors that cause model inconsistency. The analysis methods used for traditional distributed simulations are mostly empirical and qualitative, and disregard the dynamic characteristics of factor evolution in model operational running. Furthermore, distributed simulation applications (DSAs) are rapidly evolving in terms of large-scale, distributed, service-oriented, compositional, and dynamic features. Such developments present difficulty in the use of traditional analysis methods in DSAs, for the analysis of factorial effects on simulation models. To solve these problems, we construct a dynamic evolution mechanism of model consistency, called the connected model hyper-digraph (CMH). CMH is developed using formal methods that accurately specify the evolutional processes and activities of models (i.e., self-evolution, interoperability, compositionality, and authenticity). We also develop an algorithm of model consistency evolution (AMCE) based on CMH to quantitatively and dynamically evaluate influencing factors. Experimental results demonstrate that non-combination (33.7% on average) is the most influential factor, non-single-directed understanding (26.6%) is the second most influential, and non-double-directed understanding (5.0%) is the least influential. Unlike previous analysis methods, AMCE provides good feasibility and effectiveness. This research can serve as guidance for designers of consistency maintenance technologies toward achieving a high level of consistency in future DSAs.
关键词： Model consistency evolution;  Factor quantification analysis;  Connected hyper-digraph;  Formal methods;  Compositional service-oriented simulation    
Abstract: Appropriate maintenance technologies that facilitate model consistency in distributed simulation systems are relevant but generally unavailable. To resolve this problem, we analyze the main factors that cause model inconsistency. The analysis methods used for traditional distributed simulations are mostly empirical and qualitative, and disregard the dynamic characteristics of factor evolution in model operational running. Furthermore, distributed simulation applications (DSAs) are rapidly evolving in terms of large-scale, distributed, service-oriented, compositional, and dynamic features. Such developments present difficulty in the use of traditional analysis methods in DSAs, for the analysis of factorial effects on simulation models. To solve these problems, we construct a dynamic evolution mechanism of model consistency, called the connected model hyper-digraph (CMH). CMH is developed using formal methods that accurately specify the evolutional processes and activities of models (i.e., self-evolution, interoperability, compositionality, and authenticity). We also develop an algorithm of model consistency evolution (AMCE) based on CMH to quantitatively and dynamically evaluate influencing factors. Experimental results demonstrate that non-combination (33.7% on average) is the most influential factor, non-single-directed understanding (26.6%) is the second most influential, and non-double-directed understanding (5.0%) is the least influential. Unlike previous analysis methods, AMCE provides good feasibility and effectiveness. This research can serve as guidance for designers of consistency maintenance technologies toward achieving a high level of consistency in future DSAs.
Key words: Model consistency evolution    Factor quantification analysis    Connected hyper-digraph    Formal methods    Compositional service-oriented simulation
收稿日期: 2013-04-08 出版日期: 2014-01-07
CLC:  TP391.9  
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Lin-jun Fan
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Xing-tao Zhang
Jun Tang

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Lin-jun Fan, Yun-xiang Ling, Xing-tao Zhang, Jun Tang. Quantitative evaluation of model consistency evolution in compositional service-oriented simulation using a connected hyper-digraph. Front. Inform. Technol. Electron. Eng., 2014, 15(1): 1-12.

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http://www.zjujournals.com/xueshu/fitee/CN/10.1631/jzus.C1300089    或    http://www.zjujournals.com/xueshu/fitee/CN/Y2014/V15/I1/1

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