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Optimized data access for efficient execution of Semantic Services

机译:优化数据访问以有效执行语义服务

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Executing Semantic Services requires, in contrast to traditional SOAP-based Web Services, frequent read and write accesses to graph-based semantic data stores - for instance, for the evaluation of preconditions or the materialization of service effects. Therefore, the overall performance of semantic service execution, in particular for composite services, is strongly affected by the efficiency of these reads and writes. In this paper we present two data access optimization techniques for semantic data stores: Prepared Queries and Frame Caching. The former reduces the costs for repeated query evaluation, e.g., in loops. The latter provides rapid access to frequently read triples or subgraphs based on materialized views using a Frame-based data structure. The described techniques have been implemented and evaluated on the basis of OSIRIS Next, our open infrastructure for Semantic Service support.
机译:与传统的基于SOAP的Web服务相比,执行语义服务需要对基于图的语义数据存储区进行频繁的读写访问,例如,用于评估前提条件或实现服务效果。因此,语义服务执行的总体性能(尤其是对于复合服务)的整体性能会受到这些读取和写入效率的强烈影响。在本文中,我们提出了两种用于语义数据存储的数据访问优化技术:Prepared Queries和Frame Caching。前者减少了例如循环中的重复查询评估的成本。后者使用基于框架的数据结构,基于物化视图提供对频繁阅读的三元组或子图的快速访问。所描述的技术已在OSIRIS Next(我们的语义服务支持开放基础结构)的基础上实施和评估。

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