Authors: C. Ranichandra Dharmaraj; B.K. Tripathy
Addresses: School of Information Technology and Engineering, Vellore Institute of Technology, Tamil Nadu, India ' School of Computer Science and Engineering, Vellore Institute of Technology, Tamil Nadu, India
Abstract: The semantic web is built with the support of resource description framework (RDF). The changing faces of semantic web created the requirement of new approaches to store and query the RDF data. The RDF data contains large volume of data that have more number of binding. Processing the SPARQL queries over the RDF data in the cloud creates some challenges. The network cost and query processing time highly impacted the performance of queries over the cloud. This paper proposed an optimisation algorithm for query processing in the large datasets. The proposed algorithm considered the parallel execution of queries as a major objective to reduce the network cost as well as to minimise the response time of the query. The experimental evaluation is carried using the LUBM 400 university dataset along with the hardware rented with Amazon web services. The proposed algorithm proved their efficiency in terms of reducing the query response time and minimising the network traffic.
Keywords: query; SPARQL; RDF data; response time; distributed cloud.
International Journal of Advanced Intelligence Paradigms, 2023 Vol.24 No.3/4, pp.428 - 441
Received: 01 May 2017
Accepted: 02 Jan 2018
Published online: 01 Mar 2023 *