A multidimensional extension–based method for resource performance matching in cloud manufacturing

Recently, cloud manufacturing has emerged as a type of networked cooperative manufacturing process. The cloud-manufacturing environment implies very large-scale manufacturing services with various manufacturing resources appearing as cloud services and with a huge number of service-performance indexes. In reality, every cloud service is typically divided into several submodules, each of which also contains many service-performance indexes. Because this makes performance matching quite difficult, the question arises of how to select a suitable cloud service. In this work, we adopt a so-called matter-element model to describe the cloud service and the user requirement. In addition, for resource selection, we present a matching method in which module performance similarity is calculated from multidimensional extension distance. The results of a case study illustrate the implementation of the proposed method