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Materialized View Selection Using Bumble Bee Mating Optimization

Author

Listed:
  • Biri Arun

    (School of Computer and Systems Sciences, Jawaharlal Nehru University, New Delhi, India)

  • T.V. Vijay Kumar

    (School of Computer and Systems Sciences, Jawaharlal Nehru University, New Delhi, India)

Abstract

Decision support systems (DSS) constitute one of the most crucial components of almost every corporation's information system. Data warehouse provides the DSS with massive volumes of quality corporate data for analysis. On account of the volume of corporate data, its processing time of on-line analytical queries is huge (in hours and days). Materialized views have been used to substantially improve query performance. Nevertheless, selecting appropriate sets of materialized views is an NP-Complete problem. In this paper, a new discrete bumble bee mating inspired view selection algorithm (BBMVSA) that selects Top-K views from a multidimensional lattice has been proposed. Experimental results show that BBMVSA was able to select fairly good quality Top-K views incurring a lower TVEC. Materialization of the selected views would improve the overall data analysis of DSS and would facilitate the decision making process.

Suggested Citation

  • Biri Arun & T.V. Vijay Kumar, 2017. "Materialized View Selection Using Bumble Bee Mating Optimization," International Journal of Decision Support System Technology (IJDSST), IGI Global, vol. 9(3), pages 1-27, July.
    • Handle: RePEc:igg:jdsst0:v:9:y:2017:i:3:p:1-27
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    Cited by:

    1. Jay Prakash & T. V. Vijay Kumar, 2020. "Multi-objective materialized view selection using NSGA-II," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 11(5), pages 972-984, October.
    2. Akshay Kumar & T. V. Vijay Kumar, 2022. "Multi-Objective Big Data View Materialization Using MOGA," International Journal of Applied Metaheuristic Computing (IJAMC), IGI Global, vol. 13(1), pages 1-28, January.
    3. Jay Prakash & T. V. Vijay Kumar, 2020. "Multi-objective materialized view selection using MOGA," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 11(2), pages 220-231, July.

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