Estimation of Fitness Parameter along with Weight of Query Plans in Distributed Database Environment Using Genetic Algorithm Techniques

Sambit Kumar Mishra^1, , Srikanta Pattnaik² and Dulu Patnaik³

¹Department of CS&Engg, Ajay Binay Institute of Technology, Cuttack

²S.O.A. University, Bhubaneswar

³Government College of Engineering, Bhawanipatna

Cite this paper:
Sambit Kumar Mishra, Srikanta Pattnaik and Dulu Patnaik. Estimation of Fitness Parameter along with Weight of Query Plans in Distributed Database Environment Using Genetic Algorithm Techniques. American Journal of Computing Research Repository. 2015; 3(2):14-17. doi: 10.12691/ajcrr-3-2-1

Abstract

The transmission cost of the data as well as query may be similar between heterogeneous systems which may be visualized as a linear function of the size of the data. The response time of a query schedule may be seen as the time elapsed between the start of the first transmission and the time at which the attributes in the relation arrive at the required system. The minimum response time of a relation may be visualized as the minimum response time among all possible query schedules for the relation. The total time of a query schedule may be obtained as the sum of the costs of all transmissions required in the schedule. The incoming selectivity of a query schedule for a relation may be defined as the product of selectivities of all the attributes in the schedule. Usually the distribution strategy for a query consists of the schedules for all relations that may not reside in the result node used in the query. It is seen that the data transmission costs may be significantly greater than local processing costs in the system and the cost of processing a query may be determined by the transmission costs in its distribution strategy. In this paper, it is aimed to evaluate the fitness parameter along with the weight of the query plans in the distributed database environment.

Keywords:
query plan query schedule tuple join genetic algorithm attribute join

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