CBBCM: Clustering Based Automatic Service Composition

Automatic web services composition approaches aim at automatically composing services to satisfy users´ request according to the information of users´ input. As the number of web services is increasing, the performance of automatic service composition is faced with challenges. In this paper, we propose an approach based on backward chaining method to compose web services with high performance and good Qos, called Clustering Based Backward Chaining Method (CBBCM). We use k-means method to cluster services as the preliminary work. Services are clustered according to the semantic similarities of their output parameters. Skyline is used as an optimization to set services with good Qos on the top of each cluster. Then the adapted backward chaining method is applied to compose services. We evaluate our approach and the backward chaining method through experiment with different datasets. It is proved that our algorithm has a high performance and gets the composition results with better Qos.