Dynamic and Quantitative Method of Analyzing Service Consistency Evolution Based on Extended Hierarchical Finite State Automata

This paper is concerned with the dynamic evolution analysis and quantitative measurement of primary factors that cause service inconsistency in service-oriented distributed simulation applications (SODSA). Traditional methods are mostly qualitative...

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Main Authors: Linjun Fan, Jun Tang, Yunxiang Ling, Benxian Li
Format: Article
Language:English
Published: Wiley 2014-01-01
Series:The Scientific World Journal
Online Access:http://dx.doi.org/10.1155/2014/793271
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author Linjun Fan
Jun Tang
Yunxiang Ling
Benxian Li
author_facet Linjun Fan
Jun Tang
Yunxiang Ling
Benxian Li
author_sort Linjun Fan
collection DOAJ
description This paper is concerned with the dynamic evolution analysis and quantitative measurement of primary factors that cause service inconsistency in service-oriented distributed simulation applications (SODSA). Traditional methods are mostly qualitative and empirical, and they do not consider the dynamic disturbances among factors in service’s evolution behaviors such as producing, publishing, calling, and maintenance. Moreover, SODSA are rapidly evolving in terms of large-scale, reusable, compositional, pervasive, and flexible features, which presents difficulties in the usage of traditional analysis methods. To resolve these problems, a novel dynamic evolution model extended hierarchical service-finite state automata (EHS-FSA) is constructed based on finite state automata (FSA), which formally depict overall changing processes of service consistency states. And also the service consistency evolution algorithms (SCEAs) based on EHS-FSA are developed to quantitatively assess these impact factors. Experimental results show that the bad reusability (17.93% on average) is the biggest influential factor, the noncomposition of atomic services (13.12%) is the second biggest one, and the service version’s confusion (1.2%) is the smallest one. Compared with previous qualitative analysis, SCEAs present good effectiveness and feasibility. This research can guide the engineers of service consistency technologies toward obtaining a higher level of consistency in SODSA.
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institution Kabale University
issn 2356-6140
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publishDate 2014-01-01
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spelling doaj-art-2649e29dc03c430c8922e5c83a5a0d3c2025-02-03T01:01:00ZengWileyThe Scientific World Journal2356-61401537-744X2014-01-01201410.1155/2014/793271793271Dynamic and Quantitative Method of Analyzing Service Consistency Evolution Based on Extended Hierarchical Finite State AutomataLinjun Fan0Jun Tang1Yunxiang Ling2Benxian Li3Science and Technology on Information Systems Engineering Laboratory, National University of Defense Technology, Changsha 410073, ChinaDepartment of Telecommunications and Systems Engineering, Universitat Autònoma de Barcelona, 08202 Barcelona, SpainScience and Technology on Information Systems Engineering Laboratory, National University of Defense Technology, Changsha 410073, ChinaDepartment of Management Science and Engineering, Police Officer College of Chinese Armed Police Force, Chengdu 610213, ChinaThis paper is concerned with the dynamic evolution analysis and quantitative measurement of primary factors that cause service inconsistency in service-oriented distributed simulation applications (SODSA). Traditional methods are mostly qualitative and empirical, and they do not consider the dynamic disturbances among factors in service’s evolution behaviors such as producing, publishing, calling, and maintenance. Moreover, SODSA are rapidly evolving in terms of large-scale, reusable, compositional, pervasive, and flexible features, which presents difficulties in the usage of traditional analysis methods. To resolve these problems, a novel dynamic evolution model extended hierarchical service-finite state automata (EHS-FSA) is constructed based on finite state automata (FSA), which formally depict overall changing processes of service consistency states. And also the service consistency evolution algorithms (SCEAs) based on EHS-FSA are developed to quantitatively assess these impact factors. Experimental results show that the bad reusability (17.93% on average) is the biggest influential factor, the noncomposition of atomic services (13.12%) is the second biggest one, and the service version’s confusion (1.2%) is the smallest one. Compared with previous qualitative analysis, SCEAs present good effectiveness and feasibility. This research can guide the engineers of service consistency technologies toward obtaining a higher level of consistency in SODSA.http://dx.doi.org/10.1155/2014/793271
spellingShingle Linjun Fan
Jun Tang
Yunxiang Ling
Benxian Li
Dynamic and Quantitative Method of Analyzing Service Consistency Evolution Based on Extended Hierarchical Finite State Automata
The Scientific World Journal
title Dynamic and Quantitative Method of Analyzing Service Consistency Evolution Based on Extended Hierarchical Finite State Automata
title_full Dynamic and Quantitative Method of Analyzing Service Consistency Evolution Based on Extended Hierarchical Finite State Automata
title_fullStr Dynamic and Quantitative Method of Analyzing Service Consistency Evolution Based on Extended Hierarchical Finite State Automata
title_full_unstemmed Dynamic and Quantitative Method of Analyzing Service Consistency Evolution Based on Extended Hierarchical Finite State Automata
title_short Dynamic and Quantitative Method of Analyzing Service Consistency Evolution Based on Extended Hierarchical Finite State Automata
title_sort dynamic and quantitative method of analyzing service consistency evolution based on extended hierarchical finite state automata
url http://dx.doi.org/10.1155/2014/793271
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AT yunxiangling dynamicandquantitativemethodofanalyzingserviceconsistencyevolutionbasedonextendedhierarchicalfinitestateautomata
AT benxianli dynamicandquantitativemethodofanalyzingserviceconsistencyevolutionbasedonextendedhierarchicalfinitestateautomata