Dynamic Cost Ant Colony Algorithm for Optimize Distributed Database Query

  • Sayed A. MohsinEmail author
  • Saad M. DarwishEmail author
  • Ahmed YounesEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1153)


Optimizing query in distributed database is considered as the most important part of a database system. The optimizer tries to find an optimal join order which reduces the query execution cost. Many factors may affect the execution cost of a query, including communication costs, resources, and access to large distributed data sets. When the number of relations and number of joins in a query increases, the complexity of the optimizer also increases. The success of query execution heavily influenced by the search method which is performed using the query optimizer. Processing of queries is considered as NP-hard problem and many researchers are focused on this problem in recent years. Researches are trying to build an appropriate algorithm to seek an optimal solution especially when the size of the database increases. In this paper, an ant colony algorithm as one of the hybrid strategy of evolutionary algorithms is utilized to find a solution for join query optimization problem in the distributed database systems. Unlike traditional ant colony-based query optimization techniques that based on static cost, the suggested model relies on dynamic cost which calculates the cost while the execution plan is built. Using this strategy, the algorithm aims to find an optimal join order which minimizes the total execution time. Experimental results show that the proposed model can handle different number of join entities. Also, the algorithm is affected by the number of ants used. Better results are obtained in case of large joined if the number of used ants increased.


Distributed database system Join query Query optimization Ant Colony Optimization 


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© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Institute of Graduate Studies and ResearchAlexandria UniversityAlexandriaEgypt
  2. 2.Faculty of ScienceAlexandria UniversityAlexandriaEgypt

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