Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/1781
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dc.contributor.authorMurray, I-
dc.contributor.authorJayakody, A-
dc.contributor.authorHerrmann, J-
dc.contributor.authorLokuliyana, S-
dc.contributor.authorKandawala, D. S. A-
dc.contributor.authorNanayakkara, S. E. C-
dc.date.accessioned2022-03-25T06:44:02Z-
dc.date.available2022-03-25T06:44:02Z-
dc.date.issued2016-03-11-
dc.identifier.citationJ. A. D. C. A. Jayakody, I. Murray, J. Herrmann, S. Lokuliyana, D. S. A. Kandawala and S. E. C. Nanayakkara, "A database optimization model with quantitative benchmark," 2016 International Conference on Computational Techniques in Information and Communication Technologies (ICCTICT), 2016, pp. 286-291, doi: 10.1109/ICCTICT.2016.7514594.en_US
dc.identifier.isbn978-1-5090-0082-1-
dc.identifier.urihttp://rda.sliit.lk/handle/123456789/1781-
dc.description.abstractQuery 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.en_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.ispartofseries2016 International Conference on Computational Techniques in Information and Communication Technologies (ICCTICT);Pages 286-291-
dc.subjectdatabase optimizationen_US
dc.subjectmodelen_US
dc.subjectquantitative benchmarken_US
dc.titleA database optimization model with quantitative benchmarken_US
dc.typeArticleen_US
dc.identifier.doi10.1109/ICCTICT.2016.7514594en_US
Appears in Collections:Research Papers - Dept of Computer Systems Engineering
Research Papers - IEEE
Research Papers - SLIIT Staff Publications

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