Abstract

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.

Keywords:

Fuzzy clustering , multi-criterion , QoS, ranking,

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Competing interests

The authors have no competing interests.

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The authors have no competing interests.