Abstract
The loose coupling and on-demand integration are the fundamental characteristics of the Service Oriented Architecture (SOA), which have enforced rapid development of Web services. However, nonfunctional quality of service (QoS) attributes may evolve due to the changes of network conditions and locations of the service users. Some real services may update their QoS properties on-the-fly, others may turn to unavailable. Thus, addressing the problem of uninformed QoS evolution of Web services has become a significant research issue. This paper proposes a dynamic evolution framework of Web services, which uses the Collaborative Filtering (CF) to predict the QoS values and enables the evolution of Web services. In this framework, the QoS values of current users can be predicted using the past QoS data of similar users. There is no extra Web services invocation. About 1.5 millions real-world QoS data are used for evaluation and the experimental results show that it is a feasible and supplementary manner in dynamic evolution of the Web Services.
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