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Materialized View Selection using Marriage in Honey Bees 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

Data warehouse was designed to cater to the strategic decision making needs of an organization. Most queries posed on them are on-line analytical queries, which are complex and computation intensive in nature and have high query response times when processed against a large data warehouse. This time can be substantially reduced by materializing pre-computed summarized views and storing them in a data warehouse. All possible views cannot be materialized due to storage space constraints. Also, an optimal selection of subsets of views is shown to be an NP-Complete problem. This problem of view selection has been addressed in this paper by selecting a beneficial set of views, from amongst all possible views, using the swarm intelligence technique Marriage in Honey Bees Optimization (MBO). An MBO based view selection algorithm (MBOVSA), which aims to select views that incur the minimum total cost of evaluating all the views (TVEC), is proposed. In MBOVSA, the search has been intensified by incorporating the royal jelly feeding phase into MBO. MBOVSA, when compared with the most fundamental greedy based view selection algorithm HRUA, is able to select comparatively better quality views.

Suggested Citation

  • Biri Arun & T.V. Vijay Kumar, 2015. "Materialized View Selection using Marriage in Honey Bees Optimization," International Journal of Natural Computing Research (IJNCR), IGI Global, vol. 5(3), pages 1-25, July.
    • Handle: RePEc:igg:jncr00:v:5:y:2015:i:3:p:1-25
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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. Anjana Gosain & Kavita Sachdeva, 2019. "Selection of materialized views using stochastic ranking based Backtracking Search Optimization Algorithm," 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. 10(4), pages 801-810, August.
    4. 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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