Selection of materialized views using stochastic ranking based Backtracking Search Optimization Algorithm

Anjana Gosain () and Kavita Sachdeva ()
Additional contact information
Anjana Gosain: Guru Gobind Singh Indraprastha University
Kavita Sachdeva: Shree Guru Gobind Singh Tricentenary University

International Journal of System Assurance Engineering and Management, 2019, vol. 10, issue 4, No 28, 810 pages

Abstract: Abstract Selection of materialized view plays an important part in structuring decisions effectively in datawarehouse. Materialized view selection (MVS) is recognized as NP-hard and optimization problem, involving disk space and cost constraints. Numerous algorithms exist in literature for selection of materialized views. In this study, authors have proposed stochastic ranking (SR) method, together with Backtracking Search Optimization Algorithm (BSA) for solving MVS problem. The faster exploration and exploitation capabilities of BSA and the ranking method of SR technique for handling constraints are the motivating factors for proposing these two together for MVS problem. Authors have compared results with the constrained evolutionary optimization algorithm proposed by Yu et al. (IEEE Trans Syst Man Cybernet Part C Appl Rev 33(4):458–467, 2003). The proposed method handles the constraints effectively, lessens the total processing cost of query and scales well with problem size.

Keywords: Aggregation; Stochastic; Evolutionary; Constrained; Ranking; Optimization; Dimension (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s13198-019-00812-x Abstract (text/html)
Access to the full text of the articles in this series is restricted.

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:spr:ijsaem:v:10:y:2019:i:4:d:10.1007_s13198-019-00812-x

Ordering information: This journal article can be ordered from
http://www.springer.com/engineering/journal/13198

DOI: 10.1007/s13198-019-00812-x

Access Statistics for this article

International Journal of System Assurance Engineering and Management is currently edited by P.K. Kapur, A.K. Verma and U. Kumar

More articles in International Journal of System Assurance Engineering and Management from Springer, The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().