Welcome to the InfoSci Platform
Reference Hub7
Distributed Query Plan Generation using Particle Swarm Optimization

Distributed Query Plan Generation using Particle Swarm Optimization

T.V. Vijay Kumar, Amit Kumar, Rahul Singh
Copyright: © 2013 |Volume: 4 |Issue: 3 |Pages: 25
ISSN: 1947-9263|EISSN: 1947-9271|EISBN13: 9781466633889|DOI: 10.4018/ijsir.2013070104
Cite Article Cite Article

MLA

Kumar, T.V. Vijay, et al. "Distributed Query Plan Generation using Particle Swarm Optimization." IJSIR vol.4, no.3 2013: pp.58-82. http://doi.org/10.4018/ijsir.2013070104

APA

Kumar, T. V., Kumar, A., & Singh, R. (2013). Distributed Query Plan Generation using Particle Swarm Optimization. International Journal of Swarm Intelligence Research (IJSIR), 4(3), 58-82. http://doi.org/10.4018/ijsir.2013070104

Chicago

Kumar, T.V. Vijay, Amit Kumar, and Rahul Singh. "Distributed Query Plan Generation using Particle Swarm Optimization," International Journal of Swarm Intelligence Research (IJSIR) 4, no.3: 58-82. http://doi.org/10.4018/ijsir.2013070104

Export Reference

Mendeley
Favorite Full-Issue Download

Abstract

A large number of queries are posed on databases spread across the globe. In order to process these queries efficiently, optimal query processing strategies that generate efficient query processing plans are being devised. In distributed relational database systems, due to replication of relations at multiple sites, the relations required to answer a query may necessitate accessing of data from multiple sites. This leads to an exponential increase in the number of possible alternative query plans for processing a query. Though it is not computationally feasible to explore all possible query plans in such a large search space, the query plan that provides the most cost-effective option for query processing is considered necessary and should be generated for a given query. In this paper, an attempt has been made to generate such optimal query plans using Set based Comprehensive Learning Particle Swarm Optimization (S-CLPSO). Experimental comparisons of this algorithm with the GA based distributed query plan generation algorithm shows that for higher number of relations, the S-CLPSO based algorithm is able to generate comparatively better quality Top-K query plans.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.