Abstract:

To help users select the service that best satisfies their nonfunctionality requirements from a set of Web services, we propose a grey correlation analysis based QoSaware service selection method in this paper via analyzing service QoS attribute factors using the grey system theory. Based on that service QoS information is usually uncertain and incomplete, the proposed method uses intervals to model the QoS attribute values of Web services. To determine how well a service satisfies users’ concerned QoS requirements, the method firstly adopts a set of functions to normalize interval grey numbers of services’ QoS on various QoS attributes with different metrics and scales. Then it computes services’ grey incidence degree coefficients of interval grey numbers on each QoS aspects. Finally it combines each service’s grey incidence degrees on all QoS attributes to obtain an overall grey incidence degree. The service with the largest grey incidence degree is recommended to users. Compared with other Web service evaluation models, our approach is more suitable for real Web service systems where QoS information is uncertain and incomplete, and it can provide more effective and reasonable evaluation for Web service selection.

Key words: Web service;service selection;grey system theory;grey incidence degree;interval grey number