PROVIDING A FUZZY SYSTEM FOR EVALUATING AND COMBINING SERVICES IN THE SERVICE-ORIENTED ARCHITECTURE
DOI:
https://doi.org/10.32461/2226-3209.1.2018.178690Abstract
Abstract. Today, service oriented architecture is recognized as an effective way for organizations to select,
evaluate, and combine services, including key activities that take place in different phases of the service life cycle of the service oriented architecture. Service evaluation is one of the key activities in implementing a successful service project. Our goal is to assess the appropriateness of the services identified and the choice of service means using specific techniques to select a service from a set of client profiles. In this research, we are looking at how to use fuzzy logic to evaluate a set of suggested services and combine them. In order to adapt the results of the research with actual values, actual data was used.
In this paper we were able to work with the actual data by presenting a suitable combination method to achieve this goal and then, by testing this method with actual data, we were able to evaluate the efficiency of the proposed algorithm, and it was ound that this algorithm has the highest accuracy in choosing the optimal combination of services.
Keywords: Fuzzy logic, service evaluation, service mixing, service oriented architecture, service selection.
References
Abdullah, L., and Najib, L. (2014). A new type-2 fuzzy set of linguistic variables for the fuzzy analytic
hierarchy process. Expert Systems with Applications, Vol. 41, No. 7, pp. 3297-3305.
Cevik Onar, S., Oztaysi, B., and Kahraman, C. (2014). Strategic decision selection using hesitant fuzzy TOPSIS
and interval type-2 fuzzy AHP: a case study. International Journal of Computational Intelligence Systems, Vol. 7, No. 5, pp.
-1021.
Memon, M. S., Lee, Y. H., and Mari, S. I. (2015). Group multi-criteria supplier selection using combined grey
systems theory and uncertainty theory. Expert Systems with Applications, Vol. 42, No. 21, pp. 7951-7959.
F. H. Beuren, M. G. Gomes Ferreira, and P. A. Cauchick Miguel, “Product-service systems: a literature review
on integrated products and services,” Journal of Cleaner Production, vol. 47, pp. 222–231, 2013.
M.A.Amiri,and H.Serajzadeh,"QOS Aware Web Service Composition Based On Genetic Algorithm."S.l.:IEEE,
th International Symposium on Telecomunications,(2010).
I.Sora, D.Todinca, “Translating user preferences into fuzzy rules for the automatic selection of service. ”5th
international Symposium on Applied Computational Intelligence and Informatics.Timisoara, Romania, (2009).
M.Bakhshi ,F.Mardukhi and N.Nematbakhsh,” A Fuzzy-Based User-Centric Approach For Selecting The
Optimal Composition Of services”,S.l IEEE, (2010),pp. 72-79.
Z.Zheng, Y.Zhang and M.R.Lyu,"Distributed QoS Evaluation for real-world web services", in ICWS,(2010)
,pp.83-90 framework for Web services", in proceedings of the 22th IEEE Symposium on Software reliability
Engineering,(2011).
T. Kirti and S. Arun, A rule-based approach for estimating the reliability of component basedsystems, Advances
in Engineering Software, pp.24-29, 2012.
A. Seth, A. R. Singla and H. Agarwal, Service oriented architecture adoption trends: A critical survey, Proc. of
Contemporary Computing Communications in Computer and Information Science,vol.306, 2012.
Abdullah, L., and Najib, L. (2014). A new type-2 fuzzy set of linguistic variables for the fuzzy analytic
hierarchy process. Expert Systems with Applications, Vol. 41, No. 7, pp. 3297-3305.
Cevik Onar, S., Oztaysi, B., and Kahraman, C. (2014). Strategic decision selection using hesitant fuzzy TOPSIS
and interval type-2 fuzzy AHP: a case study. International Journal of Computational Intelligence Systems, Vol. 7, No. 5, pp.
-1021.
Memon, M. S., Lee, Y. H., and Mari, S. I. (2015). Group multi-criteria supplier selection using combined grey
systems theory and uncertainty theory. Expert Systems with Applications, Vol. 42, No. 21, pp. 7951-7959.
F. H. Beuren, M. G. Gomes Ferreira, and P. A. Cauchick Miguel, “Product-service systems: a literature review
on integrated products and services,” Journal of Cleaner Production, vol. 47, pp. 222–231, 2013.
M.A.Amiri,and H.Serajzadeh,"QOS Aware Web Service Composition Based On Genetic Algorithm."S.l.:IEEE,
th International Symposium on Telecomunications,(2010).
I.Sora, D.Todinca, “Translating user preferences into fuzzy rules for the automatic selection of service. ”5th
international Symposium on Applied Computational Intelligence and Informatics.Timisoara, Romania, (2009).
M.Bakhshi ,F.Mardukhi and N.Nematbakhsh,” A Fuzzy-Based User-Centric Approach For Selecting The
Optimal Composition Of services”,S.l IEEE, (2010),pp. 72-79.
Z.Zheng, Y.Zhang and M.R.Lyu,"Distributed QoS Evaluation for real-world web services", in ICWS,(2010)
,pp.83-90
framework for Web services", in proceedings of the 22th IEEE Symposium on Software reliability
Engineering,(2011).
T. Kirti and S. Arun, A rule-based approach for estimating the reliability of component basedsystems, Advances
in Engineering Software, pp.24-29, 2012.
A. Seth, A. R. Singla and H. Agarwal, Service oriented architecture adoption trends: A critical survey, Proc. of
Contemporary Computing Communications in Computer and Information Science,vol.306, 2012.
P. Bianco, R. Kotermanski and P. Merson, Evaluating a Service-Oriented Architecture, SoftwareEngineering
Institute, 2007.Trans. on Dependable Secure Comput., vol.4, pp.132-140, 2007.
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