Research And Implementation For The Technologies Of Semantic Service Discovery For Semantic Grid

With the rapid development of grid and semantic web technologies, semantic grid is emerging. Semantic Grid can be described as an extension of the current Grid in which information and services are given well-defined meaning, better enabling the cooperation of computers and people. The resources in semantic grid environment are described formally and computer process the information instead of human, making the traditional grid more intelligent. Semantic Grid is characterized by an open system, with a high degree of automation, which supports flexible collaboration and computation on a global scale. Semantic Grid makes resources be effectively shared and efficiently managed. Resources are exposed as services in Semantic Grid, and then the discovery of services is very challenging.In this paper, the architecture of sharing resources and services in semantic grid environment is presented, a model of semantic service publication and implementation is proposed and a precise matching algorithm which modifies the classical flexible matching algorithm is given, based on which the semantic services publication and discovery system is designed and implemented. This system supports semantic services publication and discovery, computes the semantic similarity of services by synthesizing the semantic similarity of inputs and outputs according to semantic similarity between concepts. The recall and precision of service discovery is greatly improved. Moreover, the system assists the creation of grid workflow and searches the concrete service for each abstract service.The main contents of our research are as follows:Firstly, the architecture of sharing resources and services in semantic grid environment is presented, which is grid workflow-oriented so that grid resources can be allocated flexibly and bound dynamically.Secondly, the model of semantic service publication and discovery is proposed. The Web Services model doesn't refer to the semantic information of services and allows only a keyword-based search of services. Since search in UDDI is restricted to keyword matching and no form of inference or flexible match between keywords can be performed, recall and precision is very low in keyword-based search. In order to improve UDDI in Web Services, we annotate services making use of ontology by the time of publishing services, and then users can search them according to precise matching algorithm.Thirdly, the precise matching algorithm of service is proposed, which modifies the flexible matching algorithm to make up its faults. Service matching in flexible matching algorithm falls into four categories. It doesn't compute the matching degree in each category. In order to resolve this problem, we compute the semantic similarity of service by synthesizing the semantic similarity of inputs and outputs according to semantic similarity between concepts.Lastly, we create meteorological ontology according to meteorological characteristics and implement the semantic service publication and discovery system based on the model of semantic service publication and discovery. Finally, we analyse the system and compare our model with UDDI.