Prefiltering Approach for Web Service Selection Based on QoS

The web service has widely spread in recent years which is showed by the large number of published web services. However, users may not always find their needs in one web service which has consequently spawned a composition of web services. This composition lead to many task difficulties including the selection of web services, which also consists of choosing the best QoS-based services among other similar services provided. From this perspective, there are several approaches to the selection of web services, however, this remains deficient at the level of execution time due to the rage number of competing web services. In this paper, we propose a new selection approach based on prefiltering and Skyline, this approach is tested and improved using a real dataset. We used two steps to solve this problem, prefiltering and Skyline. The first step is the use of K-Means clustering to bundle web services with similar Quality of Service (QoS) properties under one umbrella is explored. The second one is defining the most dominant web service using the Branch-and-Bound Skyline algorithm.