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    万长林, 史忠植, 胡 宏, 张大鹏. 基于本体的语义Web服务QoS描述和发现[J]. 计算机研究与发展, 2011, 48(6): 1059-1066.
    引用本文: 万长林, 史忠植, 胡 宏, 张大鹏. 基于本体的语义Web服务QoS描述和发现[J]. 计算机研究与发展, 2011, 48(6): 1059-1066.
    Wan Changlin, Shi Zhongzhi, Hu Hong, Zhang Dapeng. QoS-Aware Semantic Web Service Modeling and Discovery[J]. Journal of Computer Research and Development, 2011, 48(6): 1059-1066.
    Citation: Wan Changlin, Shi Zhongzhi, Hu Hong, Zhang Dapeng. QoS-Aware Semantic Web Service Modeling and Discovery[J]. Journal of Computer Research and Development, 2011, 48(6): 1059-1066.

    基于本体的语义Web服务QoS描述和发现

    QoS-Aware Semantic Web Service Modeling and Discovery

    • 摘要: WS-QMO是提出的一个用来对Web服务及其QoS信息进行建模和发现的顶层本体,它既可用于对服务QoS信息的描述和发布,也可用于对服务QoS需求的描述.WS-QMO本体基本满足了当前对Web服务QoS语义建模的普遍要求,并且由于适当地加入SWRL规则,它不但可以灵活地自定义单个QoS属性,描述一个QoS属性在不同条件下的不同取值,还可以定义复杂的组合QoS属性.相对同类本体或描述语言,它能更好地描述具有复杂约束规则的QoS属性,同时尽量利用现有的成熟规范使其定义式更为简洁.最后给出了基于该本体的QoS知识库的管理方法以及一个新的自动服务发现算法,该算法仅使用描述逻辑推理机的功能便可实现复杂约束的QoS自动服务发现,使得基于WS-QMO的Web服务建模和发现同时具备较好的描述能力和执行效率.

       

      Abstract: for the modeling of QoS-aware semantic Web service, an upper-level ontology, named as WS-QMO, is proposed to describe and publish both QoS information and QoS requirement in a semantic way. By using WS-QMO, QoS attributes and metrics are defined by OWL concepts and roles, and the QoS constraints are defined by SWRL rules. As far as we know, the WS-QMO ontology satisfies most of the current requirements for QoS-based Web service description. In addition, due to the proper integration of SWRL rules, the syntax of WS-QMO is rather concise, and it has richer description capability on complex QoS attributes comparing to the existing Web service modeling ontology. Furthermore, WS-QMO based QoS knowledge base is used in our semantic Web service architecture, which has dynamic description logic as its logic foundation. In this knowledge base, the constraint verification problem can be solved as a reasoning problem of the description logic with SWRL rules. The main KB management mechanism is built on top of the algorithms for constraint verification. More important, this mechanism comes up with a new automated Web service discovery algorithm that supports complex QoS constraints. The discovery algorithm makes a balance between semantic description capability and computational complexity.

       

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