• DocumentCode
    3584970
  • Title

    An efficient multi join query optimization for DBMS using swarm intelligent approach

  • Author

    Zager Al Saedi, Ahmed Khalaf ; Bt Ghazali, Rozaida ; Bin Mat Deris, Mustafa

  • Author_Institution
    Fac. of Comput. Sci. & Inf. Technol., Univ. Tun Hussein Onn Malaysia, Parit Raja, Malaysia
  • fYear
    2014
  • Firstpage
    113
  • Lastpage
    117
  • Abstract
    In the era of information technology, various professions are Multi Join Query Optimization (MJQO) in database management system (DBMS) such as Search engine, Data mining, Decision support system, Data warehouse and Banking system, Information retrieval (IR) make very important field to study. The increase in the amount of database and number of tables and blocks in database as well as inadequate technology have caused the multi join query optimization (MJQO) problem to remain unsolved. The problems of MJQO include the large size of queries (measure of numbers in join relation), high processing cost and long query execution time. Using swarm intelligent approaches as method to solve (MJQO) problem is practical and provide benefits for DBMS. This paper gives out a Swarm intelligence (Bees Algorithm) method towards the optimization of DBMS queries, And the propose method find Reasonable solution more efficiency than PSO algorithm, which fastest convergence rate among all known solution for MJQO. It reduces the response time of query processing. Simulation shows proposed algorithm can solve MJQO problem in less amount of time than particle swarm optimization (PSO).
  • Keywords
    database management systems; particle swarm optimisation; query processing; swarm intelligence; DBMS; MJQO; PSO; bees algorithm; database management system; information technology; multijoin query optimization; particle swarm optimization; query processing; swarm intelligent approach; Algorithm design and analysis; Computer science; Information technology; Optimization; Particle swarm optimization; Query processing; Artificial bees colony; Database Management system; Multi Join Query Optimization; Query Execution Plan; Query Execution Time; particle swarm optimization (PSO);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information and Communication Technologies (WICT), 2014 Fourth World Congress on
  • Print_ISBN
    978-1-4799-8114-4
  • Type

    conf

  • DOI
    10.1109/WICT.2014.7077312
  • Filename
    7077312