Selection of QoS Support on Artificial Immune Network Classifier for Dynamic Web Service Composition

Web services are forms of Internet software that can be integrated into a composite service using standard protocols regardless of their locations, platforms, and execution speeds to implement complex business. However, a large number of web services with similar function attributes but different QoS attributes are available, and selecting optimal component services from candidate services has become a focus in the field. In this paper, we proposed a selection method based on artificial immune network memory classifier to effectively and efficiently select services for composition, reducing the number of candidate services to be considered. We evaluate our approach experimentally using both real and synthetically generated datasets.