QOS Based Web Service Ranking Using Fuzzy C-means Clusters
نویسندگان
چکیده
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.
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