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Ant Colony-Based Approach for Query Optimization

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Data Mining and Big Data (DMBD 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9714))

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Abstract

Many approaches have been proposed aiming to reduce the cost of join operations. Such join operations represent the key factor of the inquiry process to retrieve related information from different data tables in large relational databases. Yet, there is still a need for more intelligent query optimizing approaches to reduce the response time of query execution. This paper proposes an approach for reaching optimal query access plans for complex relational database queries including a set of join operations. The proposed approach is based on ant colony optimization technique to benefit from its ability of parallel search over several constructive computational threads which aims to reach an optimal query access plan. A comparative study shows the added value of the proposed approach.

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Authors and Affiliations

  1. Computer Science Department, ISSR, Cairo University, Giza, Egypt

    Hany A. Hanafy & Ahmed M. Gadallah

Authors
  1. Hany A. Hanafy
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  2. Ahmed M. Gadallah
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Correspondence to Hany A. Hanafy .

Editor information

Editors and Affiliations

  1. Peking University, Beijing, China

    Ying Tan

  2. Xi'an Jiaotong-Liverpool University, Suzhou, China

    Yuhui Shi

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© 2016 Springer International Publishing Switzerland

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Hanafy, H.A., Gadallah, A.M. (2016). Ant Colony-Based Approach for Query Optimization. In: Tan, Y., Shi, Y. (eds) Data Mining and Big Data. DMBD 2016. Lecture Notes in Computer Science(), vol 9714. Springer, Cham. https://doi.org/10.1007/978-3-319-40973-3_43

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  • DOI: https://doi.org/10.1007/978-3-319-40973-3_43

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-40972-6

  • Online ISBN: 978-3-319-40973-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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