Research On Related Technologies Of Service Discovery In Multi-Ontology Environment

With the rapid growth of network technologies, Internet especially, service-oriented computing became one of popular distributed computing technology. And application progress raised new challenges to service-oriented computing, such as automatization of service, seamless collaboration of servies, and so on. Ontology, which is the shared formal conceptual model of a domain, is an effective tool to automatize service discovery, composition, monitor and achieve semantic interoperability among services. However, due to the open characteristic of Internet, autonomic users construct their own ontologies of the same or overlapped domain according their own requirements, and the collaboration among applications would break the bound of domain and occur across ontologies. Therefore the fact of multiple ontologies coexisting is one of the most important issues of applications collaboration in open distributed computing environment.Multiple coexistent ontologies challenge service-oriented computing, especially service discovery based on ontology. Firstly, ontology interoperability is the essential basis of service discovery mechanism in multi-ontology environment. Secondly, service disocovery mechanism in multi-ontoltogy environment should support multiple ontologies and service matching across ontologies. And services in multiontology environment should be well organized. At the same time, it must provide an acceptable efficiency and validity of service matching.Aiming to these related technologies of "service discovery in multi-ontology environment", the primary work and contributions of this dissertation include:(1) Because few available approaches of ontology interoperability took relations among ontologies into account, a hierarchical ontology model (HOM) is proposed to formally describe these relationships. Based on HOM, a revised ontology mapping algorithm HOM-Matching is brought forward. HOM-Matching is based HOM, and utilizing the relations between ontologies in calculating semantic similarity between ontology entities. The experimental results shown that while the aligned ontologies share the imported ontologies, HOM-Matching will improve the F-Measure of ontology mapping.(2) To support multiple coexistent ontologies, organize services well and enable service discovery across ontology, a service discovery architecture based on ontology community, named as SSD_OC, is proposed. SSD_OC divides services into different ontology communities according to the ontologies which service referred to, and bridges ontology communities using mappings between ontologies. Further, ontology transformation between ontology communities is used to achieve service matching across ontologies. Within ontology community, it extends UDDI to support service matching based on ontology. SSD_OC can support multiple coexistent ontology and service discovery across ontology. Experiemtal results show that service discovery mechanism in SSD_OC improves the Recall and F-Measure of service matching due to service matching across ontology. And SSD_OC is scalable for it practices a policy of "Divide and Conqure".(3) To ease the bottleneck effect of centralized service registers and improve the performance of service discovery across ontologies, a two layered P2P model for service discovery is proposed in this disssertation. The model is based on SSD_OC and integrates iVCE (Internet-based virtual computing environment) core concepts into a P2P model. Based on this model, a service discovery algorithm composing two stages and three steps is proposed. It matches services across communities as well as within community. Within a community, after locating registers holding service information with a high probability of satisfying a request, algorithm captures semantic matching between service advertisements and service requests by logical reasoning. Service discovery across communities occurs according to some policies. The model is suitable for opening environment with coexistent multiple ontologies. Experimental results show that given an appropriate setting, the model would make a tradeoff between recall and responding time. In addition, the model would release the mean load of registers efficiently while holding recall.(4) Finally, taking QoS of service as research object, and aiming to the particularity of QoS, a hierarchical ontology model for QoS, which is based on HOM and called as QoSHOnt, is proposed in this dissertation. QoSHOnt consists of three components: QoS Upper Ontology in QoS Core Layer, QoS Middle Ontology in QoS Attribute Layer and QoS Lower Ontology in QoS User Layer. With hierarchy, QoSHOnt guarantee the consistence of QoS model in QoS attribute layer and diversity in QoS user layer. In addition, for QoSHOnt models QoS attributes in different context, it would support Service Level Agreement (SLA) well. Based on this model, a QoS-matching and service selection algorithm is proposed. Finally a service discovery framework based on ontology is illustrated. The framework support domain ontology as well as QoS ontology.