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Evaluation of gene value and heuristic function of alternate plans in multi database system using Genetic Algorithm

Evaluation of gene value and heuristic function of alternate plans in multi database system using Genetic Algorithm

ISSN : 0975-5705
Journal from gdlhub / 2017-08-14 11:52:33
Oleh : Sambit Kumar Mishra and Srikanta Pattnaik, International Journal of Database Management Systems
Dibuat : 2012-06-26, dengan 1 file

Keyword : Evaluation of operating theater design, planning of operating theater, New trends in operating theater design
Subjek : Evaluation of gene value and heuristic function of alternate plans in multi database system using Genetic Algorithm
Url : http://airccse.org/journal/ijdms/papers/3311ijdms07.pdf
Sumber pengambilan dokumen : Internet

The major tasks in multiple query processing in multi database system are common operation or expression


identification and global execution plan construction. Each query can have several alternative evaluation


plans, each with a different set of tasks. Therefore the goal of multiple query processing is to choose the


right set of plans for queries which minimizes the total execution time by performing common tasks only


once. The objectives in the multiple query processing are to increase system throughput and decrease


single query response time. I have retrieved the alternate plans and the tasks, estimated cost of plans and


heuristic function of alternate plans in multi database system by applying the genetic algorithm technique.

Deskripsi Alternatif :

The major tasks in multiple query processing in multi database system are common operation or expression


identification and global execution plan construction. Each query can have several alternative evaluation


plans, each with a different set of tasks. Therefore the goal of multiple query processing is to choose the


right set of plans for queries which minimizes the total execution time by performing common tasks only


once. The objectives in the multiple query processing are to increase system throughput and decrease


single query response time. I have retrieved the alternate plans and the tasks, estimated cost of plans and


heuristic function of alternate plans in multi database system by applying the genetic algorithm technique.

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