Service evaluation-based resource selection in cloud manufacturing

Abstract

With the development of cloud computing, cloud manufacturing has been gained more and more attention. According to the peculiarity of cloud manufacturing, the resource designated as manufacturing service is always massive, complex and heterogeneous, and the high degree of user participation, and user diversity are also the main features. This paper presents a method of resource selection based on service evaluation, which consists of predictive evaluation and recommended evaluation. In detail, predictive evaluation is based on user's historical service evaluations which may have different influence according to the experience in different time. Recommended evaluation is given by the recommenders who are generated by 2-step selection and have different recommended weight according to their similarities and objectivities. Finally, experiment results show that the proposed algorithm has better performance.