A web service selection approach based on improved Euclidean distance

With the development of Internet, web service is used widely. How to choose the web service which can satisfy the non-functional requirement of users is an important problem in web service. To address this problem, this paper presents a web service selection approach based on improved Euclidean distance. It uses the gauss method to normalize the multi-dimension QoS parameters and computes the distance of points in the multidimension QoS space to scale the similarity of QoS properties by introducing weight to Euclidean distance. Then the web service which can satisfy the non-functional requirement of users can be found according to this approach. At last, an application example is used to explain this approach.