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Enhanced query processing using weighted predicate tree in edge computing environment

机译:边缘计算环境中使用加权谓词树的增强查询处理

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Edge computing is a novel computing paradigm in which the edge nodes of Internet of Things (IoT) are heavily involved in data processing. Resource Description Framework (RDF) plays an important role in Semantic Web due to the explosive growth of data of IoT. RDF is a graph-based data model employed for representing the Uniform Resource Identifiers (URIs), and SPARQL is the standard query language used for processing the query of RDF data. Growth of data throws a big challenge to the data storing and processing. In this paper a new data storing and query processing approach is proposed using weighted predicate tree. The predicate tree is used for effective storing of data and extracting the weights indicating the relation of the data. Computer simulation with SP2 Bench data set and SPARQL query reveals that the proposed approach allows substantially higher performance than three existing representative query processing schemes.
机译:边缘计算是一种新颖的计算范例,其中:内容的Internet(物联网)的边缘节点大量涉及数据处理。资源描述框架(RDF)由于IOT数据的爆炸性增长,在语义网上扮演着重要作用。 RDF是用于表示统一资源标识符(URI)的基于图形的数据模型,SPARQL是用于处理RDF数据查询的标准查询语言。数据的增长对数据存储和处理产生了重大挑战。在本文中,使用加权谓词树提出了一种新的数据存储和查询处理方法。谓词树用于有效地存储数据并提取指示数据关系的权重。具有SP 2 台式数据集和SPARQL查询的计算机模拟显示,所提出的方法允许比现有的三个代表查询处理方案的性能显着更高。

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