Abstract
Various resource description framework (RDF) partitioning methods have been studied for the efficient distributed processing of a large RDF graph. The RDF graph has symmetrical characteristics because subject and object can be used interchangeably if predicate is changed. This paper proposes a dynamic partitioning method of RDF graphs to support load balancing in distributed environments where data insertion and change continue to occur. The proposed method generates clusters and subclusters by considering the usage frequency of the RDF graph that are used by queries as the criteria to perform graph partitioning. It creates a cluster by grouping RDF subgraphs with higher usage frequency while creating a subcluster with lower usage frequency. These clusters and subclusters conduct load balancing by using the mean frequency of queries for the distributed server and conduct graph data partitioning by considering the size of the data stored in each distributed server. It also minimizes the number of edge-cuts connected to clusters and subclusters to minimize communication costs between servers. This solves the problem of data concentration to specific servers due to ongoing data changes and additions and allows efficient load balancing among servers. The performance results show that the proposed method significantly outperforms the existing partitioning methods in terms of query performance time in a distributed server.
Highlights
Web technology has continuously evolved, and a variety of information has become available on the web with the increasing number of web users and amount of information on the web
We propose a method to collect the information of the subgraph used in the query to perform the partition using the resource description framework (RDF) graph usage pattern
We propose a detailed algorithm for creating clusters and subclusters, and propose a partitioning method using clusters and subclusters
Summary
Web technology has continuously evolved, and a variety of information has become available on the web with the increasing number of web users and amount of information on the web. The general web service has provided information suitable for users’ search needs through hyperlinks among information resources; it has been associated with difficulties in terms of accurate information searches and the meaningful interpretation of information. A next-generation web that can meet users’ various needs and support more accurate searches is needed. The semantic web is under the spotlight as an alternative to the next-generation web [1,2]. It can define meaningful relationships among data and generate new knowledge through reasoning [3,4]. As metadata and ontology play a core role in the semantic web, the resource description framework (RDF) was proposed by the World Wide Web Consortium (W3C) to describe web data formally [5,6,7]
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