An Improved Approach for QoS Based Web Services Selection Using Clustering
Mourad Fariss, Naoufal El Allali, Hakima Asaidi, Mohamed Bellouki · Advances in Science Technology and Engineering Systems Journal · 2021
With the rising number of web services created to build complex business processes, selecting the appropriate web service from a large number of web services respond to the same client request with the same functionality are developed independently but with different quality of service (QoS) attributes.From this point, there are many approaches to web service selection.Nevertheless, this is still deficient due to a considerable number of discovered web services.The prefiltering is a solution to reduce the number of web services candidates.In this paper, the K-means clustering is applied to determine similar services based on QoS information.The results of this prefiltering are considered at the selection task using the Branch and Bound Skyline (BBS) algorithm.The experimental evaluation performed on real Dataset proves that our approach presents efficient results for web service selection.