A database optimization model with quantitative benchmark

Jayakody, J.; Murray, Iain; Herrmann, J.; Lokuliyana, S.; Kandawala, D.; Nanayakkara, S.

doi:10.1109/ICCTICT.2016.7514594

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Access Status

Open access

Authors

Jayakody, J.

Murray, Iain

Herrmann, J.

Lokuliyana, S.

Kandawala, D.

Nanayakkara, S.

Date

2016

Type

Conference Paper

Metadata

Show full item record

Citation

Jayakody, J. and Murray, I. and Herrmann, J. and Lokuliyana, S. and Kandawala, D. and Nanayakkara, S. 2016. A database optimization model with quantitative benchmark, in Proceedings of the International Conference on Computational Techniques in Information and Communication Technologies (ICCTICT), Mar 11-13 2016, pp. 286-291. New Delhi, India: IEEE.

Source Title

2016 International Conference on Computational Techniques in Information and Communication Technologies, ICCTICT 2016 - Proceedings

DOI

10.1109/ICCTICT.2016.7514594

ISBN

9781509000821

School

Department of Electrical and Computer Engineering

Remarks

Copyright © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

URI

http://hdl.handle.net/20.500.11937/17197

Collection

Curtin Research Publications

Abstract

Query optimization and indexing have an immense impact on database optimization. This has been considered in many different perspectives which provide several different solutions in each case. The purpose of this paper is to primarily provide a comprehensive review and discussion of the core problems through the research on query optimization technology and indexing, based on a number of optimization techniques commonly used in the general approach of a query. A new database optimization model is designed and experiments show that this model can significantly reduce the amount of query execution time to improve the optimization efficiency. Regardless of research on the database optimization model, significant work has been done to comparatively evaluate three scenarios; non-optimized query, optimized query without following any optimization standard, and optimized query via proposed optimization model using the same experimental methodology. Further, this paper describes a benchmark that was developed specifically for the purpose of measuring the quantitative evaluations of the proposed database optimization model.