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Abstract
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Article Information:
QOS Based Web Service Ranking Using Fuzzy C-means Clusters
P. Parameswari and J. Abdul Samath
Corresponding Author: P. Parameswari
Submitted: March 19, 2015
Accepted: April 14, 2015
Published: July 25, 2015 |
Abstract:
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In service oriented computing ranking of best service from service registry is an essential process for service selection. The main objective of this research is to select a best service using fuzzy C-Means clustering. Identifying the best web service among all the existing services is a challenging issue. In the existing system, the ranking process uses a static priority of QoS parameters to find the best service. The first challenge is the customized prioritization of the QoS parameters and the second challenge is the multi-criterion analysis of the data. The proposed system identifies the best service using customized priority. The best service is obtained through a two-level process using fuzzy, c-means clustering algorithm for multi-criterion analysis and the threshold is calculated through the Manhattan distance algorithm. The empirical evaluation of the proposed system concludes that it reduces the time for service ranking.
Key words: Fuzzy clustering, multi-criterion, QoS, ranking, , ,
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Cite this Reference:
P. Parameswari and J. Abdul Samath, . QOS Based Web Service Ranking Using Fuzzy C-means Clusters. Research Journal of Applied Sciences, Engineering and Technology, (9): 1045-1050.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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