Special Issue Article Open Access

Single Query Optimization of SPARQL Using Ant Colony Optimization

Abstract

As increasingly large RDF datasets are being published on the web, efficient RDF querying has become an essential factor in realizing the semantic web. One of the reasons of slow speeds of executions could be excess normalization leading to single tables. More the number of tables more are the complex nature of joins, and thus leading to more execution times. So to retrieve data quickly, there is a need to optimize the query. Query optimization is the refining process in database administration and it helps to bring down speed of execution Query optimization is performed translating the SQL queries in to query tree. Then pick the best algorithm for optimization of queries. In this paper we are used a meta heuristic technique Ant Colony Optimization (ACO) .The proposed technique is efficient and scalable for SPARQL query by using with ACO.

Ms.P R Rupashini, Mrs. R Gomathi

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