Optimization of Different Queries using Optimization Algorithm (DE)

The biggest challenge in modern web is to tackle tremendous growth of data, scattered and continuously updating in nature. Processing of such unscattered data by human or machine remains a tedious task. Semantic Web; as a solution has already been invented. But, still there are some other challenges, like as optimization of the query. We introduce a new approach for real–time SPARQL query optimization with different forms and different triple patterns. The strategy introduces rearrangement of order of triple pattern using Differential Evolution(DE). The experimental study focus on main-memory model of RDF data and ARQ query engine of Jena. We compare the result of proposed approach with the Ant Colony Optimization(ACO) different versions and some other approaches. Results shows that proposed approach provides better execution time as compare to the other approaches.