Optimization of Distributed Database Queries Using Hybrids of Ant Colony Optimization Algorithm

With the advancement of Computer Networks and increase in size of databases, the decentralization of databases has led to the development of Distributed Database over multiple machines where distribution of the database is Transparent to the users. The query optimization problem in large-scale distributed databases is NP-hard in nature and difficult to solve. Research is being carried out to find an appropriate algorithm to seek an optimal solution especially when the size of the database increases [4].An Ant Colony Optimization Algorithm meets the requirement mentioned above because of its characteristics of positive feedback, distributed computing and combination with heuristics. However, when ACO is implemented in Distributed Database queries, the Initial Information needed by ACO to generate an optimal result set is not systematic and organized which leads to slower convergence speed in the beginning of the processing to generate an optimal solution. In this paper, hybrids of Ant Colony optimization strategies implemented in Distributed Database are reviewed and studies show that the performance of distributed query optimization is improved when ACO is integrated with other optimization algorithms. Keywords— Distributed Database, Query Optimization, Ant Colony Optimization Algorithm, Hybrid of ACO, Optimization Strategies