Query Optimization: An Intelligent Hybrid Approach using Cuckoo and Tabu Search
Mukul Joshi and
Praveen Ranjan Srivastava
Additional contact information
Mukul Joshi: Department of Computer Science and Information System, Birla Institute of Technology & Science, Pilani Rajasthan, India
Praveen Ranjan Srivastava: Department of Computer Science and Information System, Birla Institute of Technology & Science, Pilani Rajasthan, India
International Journal of Intelligent Information Technologies (IJIIT), 2013, vol. 9, issue 1, 40-55
Abstract:
Query optimization is an important aspect in designing database management systems, aimed to find an optimal query execution plan so that overall time of query execution is minimized. Multi join query ordering (MJQO) is an integral part of query optimizer. This paper aims to propose a solution for MJQO problem, which is an NP complete problem. This paper proposes a heuristic based algorithm as a solution of MJQO problem. The proposed algorithm is a combination of two basic search algorithms, cuckoo and tabu search. Simulation shows some exciting results in favour of the proposed algorithm and concludes that proposed algorithm can solve MJQO problem in less amount of time than the existing methods.
Date: 2013
References: Add references at CitEc
Citations:
Downloads: (external link)
https://services.igi-global.com/resolvedoi/resolve ... 4018/jiit.2013010103 (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:igg:jiit00:v:9:y:2013:i:1:p:40-55
Access Statistics for this article
International Journal of Intelligent Information Technologies (IJIIT) is currently edited by Vijayan Sugumaran
More articles in International Journal of Intelligent Information Technologies (IJIIT) from IGI Global
Bibliographic data for series maintained by Journal Editor ().