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The Scientific World Journal
Volume 2014 (2014), Article ID 793271, 11 pages
http://dx.doi.org/10.1155/2014/793271
Research Article

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

1Science and Technology on Information Systems Engineering Laboratory, National University of Defense Technology, Changsha 410073, China
2Department of Telecommunications and Systems Engineering, Universitat Autònoma de Barcelona, 08202 Barcelona, Spain
3Department of Management Science and Engineering, Police Officer College of Chinese Armed Police Force, Chengdu 610213, China

Received 9 September 2013; Accepted 19 November 2013; Published 8 January 2014

Academic Editors: B. Johansson and P. Liu

Copyright © 2014 Linjun Fan et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

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.