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CLC number: TP391.9

On-line Access: 2014-01-07

Received: 2013-04-08

Revision Accepted: 2013-08-20

Crosschecked: 2013-12-16

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Journal of Zhejiang University SCIENCE C 2014 Vol.15 No.1 P.1-12


Quantitative evaluation of model consistency evolution in compositional service-oriented simulation using a connected hyper-digraph

Author(s):  Lin-jun Fan, Yun-xiang Ling, Xing-tao Zhang, Jun Tang

Affiliation(s):  Science and Technology on Information Systems Engineering Laboratory, National University of Defense Technology, Changsha 410073, China; more

Corresponding email(s):   ljfan_nudt@163.com, yxling@tom.com, zhangxingtaolyx@163.com, 08202tangjun018@gmail.com

Key Words:  Model consistency evolution, Factor quantification analysis, Connected hyper-digraph, Formal methods, Compositional service-oriented simulation

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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[J]. Journal of Zhejiang University Science C, 2014, 15(1): 1-12.

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author="Lin-jun Fan, Yun-xiang Ling, Xing-tao Zhang, Jun Tang",
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publisher="Zhejiang University Press & Springer",

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%T Quantitative evaluation of model consistency evolution in compositional service-oriented simulation using a connected hyper-digraph
%A Lin-jun Fan
%A Yun-xiang Ling
%A Xing-tao Zhang
%A Jun Tang
%J Journal of Zhejiang University SCIENCE C
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%@ 1869-1951
%D 2014
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.C1300089

T1 - Quantitative evaluation of model consistency evolution in compositional service-oriented simulation using a connected hyper-digraph
A1 - Lin-jun Fan
A1 - Yun-xiang Ling
A1 - Xing-tao Zhang
A1 - Jun Tang
J0 - Journal of Zhejiang University Science C
VL - 15
IS - 1
SP - 1
EP - 12
%@ 1869-1951
Y1 - 2014
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.C1300089

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.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


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