IDEAS home Printed from https://ideas.repec.org/a/spr/ijsaem/v11y2020i5d10.1007_s13198-020-01030-6.html
   My bibliography  Save this article

Multi-objective materialized view selection using NSGA-II

Author

Listed:
  • Jay Prakash

    (Jawaharlal Nehru University)

  • T. V. Vijay Kumar

    (Jawaharlal Nehru University)

Abstract

Data warehouse is constructed with the purpose of supporting decision making. Decision making queries, being long and complex, consume a lot of time in processing against a continuously growing data warehouse. View materialization is one of the alternative ways of improving the response time of such analytical or decision making queries. This involves selection and materialization of views that minimize the analytical query response times while adhering to the resource constraints. This is referred to as the view selection problem, which is a NP-Hard problem. The view selection problem is concerned with simultaneously minimizing the cost of evaluating materialized and non-materialized views. This being a bi-objective optimization problem is addressed using NSGA-II in this paper. The proposed approach aims to achieve an acceptable trade-off between the afore-mentioned two objectives.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:ijsaem:v:11:y:2020:i:5:d:10.1007_s13198-020-01030-6
    DOI: 10.1007/s13198-020-01030-6
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s13198-020-01030-6
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s13198-020-01030-6?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Mohammad Haider Syed & T.V. Vijay Kumar, 2017. "Query Frequency based View Selection," International Journal of Business Analytics (IJBAN), IGI Global, vol. 4(1), pages 36-55, January.
    2. Biri Arun & T.V. Vijay Kumar, 2017. "Materialized View Selection using Artificial Bee Colony Optimization," International Journal of Intelligent Information Technologies (IJIIT), IGI Global, vol. 13(1), pages 26-49, January.
    3. T.V. Vijay Kumar, 2013. "Answering query-based selection of materialised views," International Journal of Information and Decision Sciences, Inderscience Enterprises Ltd, vol. 5(1), pages 103-116.
    4. 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.
    5. Biren Shah & Karthik Ramachandran & Vijay Raghavan, 2006. "A Hybrid Approach for Data Warehouse View Selection," International Journal of Data Warehousing and Mining (IJDWM), IGI Global, vol. 2(2), pages 1-37, April.
    6. 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.
    7. T.V. Vijay Kumar & Kalyani Devi, 2012. "Materialised view construction in data warehouse for decision making," International Journal of Business Information Systems, Inderscience Enterprises Ltd, vol. 11(4), pages 379-396.
    8. T.V. Vijay Kumar & Santosh Kumar, 2015. "Materialised view selection using randomised algorithms," International Journal of Business Information Systems, Inderscience Enterprises Ltd, vol. 19(2), pages 224-240.
    9. T.V. Vijay Kumar & Biri Arun, 2016. "Materialised view selection using BCO," International Journal of Business Information Systems, Inderscience Enterprises Ltd, vol. 22(3), pages 280-301.
    10. T. V. Vijay Kumar & Biri Arun, 2017. "Materialized view selection using HBMO," 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. 8(1), pages 379-392, January.
    11. T.V. Vijay Kumar & Mohammad Haider, 2015. "Query answering-based view selection," International Journal of Business Information Systems, Inderscience Enterprises Ltd, vol. 18(3), pages 338-353.
    12. 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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. T. V. Vijay Kumar & Biri Arun, 2017. "Materialized view selection using HBMO," 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. 8(1), pages 379-392, January.
    3. 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.
    4. 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.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:ijsaem:v:11:y:2020:i:5:d:10.1007_s13198-020-01030-6. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.