A New Method of Genetic Algorithm for Data Allocation in Distributed Database Systems

摘要

The important problem of distributed database systems (DDBs) is "data allocation". There are many methods for this problem and there are two measures for compare these models: Minimal cost and Performance. In this paper we use a new method for using genetic algorithm. At first we generate clusters based on the communication cost between the sites, then perform genetic algorithm on these clusters to find which one is the best situation for allocate data, at last allocate data to their sites in the same way. We improve performance of DDB with reduce number of communication cost, data redundancy, and minimize total data transfer cost by using genetic algorithm and grouping sites. We compare our results with another model; our proposal model has a higher performance.