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Query Optimization using Modified Ant Colony Algorithm

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2017
Authors:
Ajay Wagh, Varsha Nemade
10.5120/ijca2017914185

Ajay Wagh and Varsha Nemade. Query Optimization using Modified Ant Colony Algorithm. International Journal of Computer Applications 167(2):29-33, June 2017. BibTeX

@article{10.5120/ijca2017914185,
	author = {Ajay Wagh and Varsha Nemade},
	title = {Query Optimization using Modified Ant Colony Algorithm},
	journal = {International Journal of Computer Applications},
	issue_date = {June 2017},
	volume = {167},
	number = {2},
	month = {Jun},
	year = {2017},
	issn = {0975-8887},
	pages = {29-33},
	numpages = {5},
	url = {http://www.ijcaonline.org/archives/volume167/number2/27745-2017914185},
	doi = {10.5120/ijca2017914185},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

Query optimization is challenging task in database. Many different types of techniques used to optimize query. Heuristic Greedy, Iterative Improvement and Ant Colony algorithms is being used to query optimization. Ant colony Algorithm used to find optimal solution for different type of problems. In this paper we modify Ant Colony Algorithm for query optimization and will show the comparison execution time between Heuristic based optimization, Ant Colony Optimization and Modified Ant Colony optimization algorithms. After implementation of said existing algorithms and modified Ant Colony optimization algorithms we found that modified Ant colony taking less computation time as compare to others algorithms.

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Keywords

Query Optimization, Heuristic-based optimizers, Ant-Colony, Modified Ant Colony.