Optimal Ant and Join Cardinality for Distributed Query Optimization Using Ant Colony Optimization Algorithm

Abstract

Query Optimization in Distributed Database Management System (DDBMS) involving large number of relations with multiple joins has always been an attractive area of research. Ants are the social agents in Ant Colony Optimization Algorithm that are responsible for generating optimized solutions to the problem under study. The appropriate numbers of ants needed to generate optimal solutions in terms of both join cardinality, response time is continuously under consideration by researchers as small number of ants leads to premature convergence, and large number of ants leads to high exploration causing slower convergence. This paper attempts to estimate minimum number of ants needed to optimize distributed queries with varied number of joins. This estimation is coined as Ant Ratio, which evaluates the requirement of x number of ants for optimizing distributed query with y number of joins.