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Materialized View Selection Using Backtracking Search Optimization Algorithm

  • Anjana Gosain
  • Kavita Sachdeva
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 695)

Abstract

Selecting the materialized views optimally is very important in designing a data warehouse and is NP-hard problem. Various evolutionary algorithms exist in literature for the appropriate selection of materialized views. In this paper, we have examined the application of backtracking search optimization algorithm (BSA), for selecting the materialized views in data warehouse. According to our experiments, the results obtained by our proposed backtracking search optimization-based materialized view selection algorithm (BSMVSA) are superior to those found using particle swarm optimization and genetic algorithm. The solution obtained by BSMVSA greatly reduces the total cost within the storage constraint.

Keywords

Aggregation Dimension Measure Heuristic Evolutionary 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.University School of Information and Communications TechnologyGGS Indraprastha UniversityNew DelhiIndia

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