Service-evaluation-based resource selection for cloud manufacturing. (December 2016) - Zhao, Yan-Wei; Zhu, Li-Nan
With the development of cloud computing, increasing attention has shifted from traditional manufacturing toward cloud manufacturing. The distinguishing feature of cloud manufacturing is that the resource designated for a given manufacturing service is always massive, complex, and heterogeneous. Cloud manufacturing also involves a high degree of user participation and user diversity. This article presents a method of resource selection based on service evaluation, which combines predictive evaluations and recommended evaluations. Predictive evaluations are based on the user's historical evaluations of a given service, and these evaluations may be weighted differently depending on the time when the service occurred. Recommended evaluations are given by recommenders who are selected by a two-step process. These evaluations are weighted according to their similarities and objectivities. The results of numerical experiments show that the proposed method performs better than previous methods.