Impact of Varying Parameters in Improved Multi Colony Ant Optimization Algorithm for Join Order Problem in Distributed Databases

Query Optimization in Distributed Databases is a challenging task due to the rising size of the database. The join operation has a great significance for the execution of queries containing multiple relations. An optimizer may suggest many join order for a single query and selects the best join order that executes the query in minimum time. The current optimizers are working well with a lesser number of relations but as the number of relations in a query increases, execution time also increases. To reduce this execution time, optimizers are required to redesigned or altered. In this paper, an improved existing algorithm is described to deal with the join order problem in Query Optimization and is based on the Multi Colony Ant Optimization algorithm. The performance of the proposed algorithm depends on various parameters such as the number of iterations, number of colonies, and Ant ratio. In this paper, the impact of these parameters on an improved algorithm is also described.