Study of manufacturing cloud service matching algorithm based on OWL-S

Under the cloud manufacturing environment, with the increasing number of manufacturing cloud services, one of the issues needs to be resolved is to find a manufacturing cloud service that meets users´ demand. However, until now, there is not an outstanding manufacturing cloud discovery mechanism to help users to find the appropriate solution among numerous existing manufacturing cloud services. In order to realize manufacturing cloud services rapidly, efficiently and accurately match, a multi-level intelligent matching method was proposed in this paper. This method includes 3 parts: (1) a service describing model based on OWL (Ontology Web Language) aiming at the diversity dynamic characteristics of manufacturing cloud service, which includes base information, state function, QoS (Quality of Service); (2) the describing information is classified into 4 categories, word information, sentence information, number information and fuzzy information, and its corresponding similarity matching algorithms is given respectively; (3) based on the above similarity algorithms, a five-step manufacturing cloud service matching processes such as basic matching, state matching, functional matching, QoS matching and integrated matching, was proposed. Case study and analysis demonstrate that the proposed algorithm is more efficient and accurate than that of the existing ones.