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Modeling Location Preferences in Service Composition Using Distributed Knowledgebase

机译:使用分布式知识库在服务组合中建模位置首选项

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Successful Composition of a web service in dynamic environment is a big challenge and important research issue. Several service designers may produce similar or different services. In automatic service selection environment service may fail due to functional dissimilarity and non-functional property of the services (QoS) attributes. In this context, any service can be preferred for particular location. These preferences act as QoS attribute and play important role to minimize failure of the service. Knowledge of these location preferences also helps in dynamic service selection. In composition, services are present in heterogeneous environment with different location preferences. In this paper, we have developed a knowledge base for the location preferences, which we have termed as Location Affinity. We have also incorporated semantic matching phenomenon along with affinity matching of the service for distributed environment using distributed description logic.
机译:动态环境中Web服务的成功组合是一个巨大的挑战,也是一个重要的研究课题。几个服务设计者可能会提供相似或不同的服务。在自动服务选择环境中,服务可能由于服务(QoS)属性的功能差异和非功能属性而失败。在这种情况下,对于特定位置,任何服务都可以是首选。这些首选项充当QoS属性,并在最小化服务故障方面起着重要作用。这些位置首选项的知识也有助于动态服务选择。在组成上,服务存在于具有不同位置首选项的异构环境中。在本文中,我们为位置偏好开发了一个知识库,我们称之为位置亲和力。我们还使用分布式描述逻辑将语义匹配现象与服务的亲和力匹配合并到分布式环境中。

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