A QoS-based neuro-fuzzy model for ranking Web services

Quality-of-Service (QoS) is widely employed for describing non-functional characteristics of Web services. Web Service selection and evolution is receiving huge interest in the service oriented architecture community due to dynamic and volatile web service environment. The automatic selection and composition of Web services rely strongly on the manner to deal with ambiguity inherent to the description of functionalities of these services and the client´s requests. Quality of Service (QoS) criteria become crucial in Web services selection and the problem of checking that a web service satisfies a given level of QOS is considered in recent research works. This paper presents a QoS based automatic classification method of web services. These services give generally similar functionalities and are offered by different providers. The main feature of our Web service selection model is to take advantage of the neuro-fuzzy logic for coping with the imprecision of QoS constraints values.