Materializing Multi Join Query Optimization for RDBMS Using Swarm Intelligent Approach

Abstract

In the era of Information Technology (IT), various professions are Multi Join Query Optimization (MJQO) in database management system (DBMS) such as Decision support system, Data warehouse, Data mining, banking system, Information retrieval (IR), marketing and more. The increase in database amount, number of tables, blocks in database and the size of query make MJQO appear. MJQO aimed to find optimal Query execution plan (QEP) in minimum query execution time. The objective of this study proposes optimal solution approach to solve MJQO problem, which is an NP hard problem. This study propose Swarm Intelligence (SI) as a solution of MJQO problem. Artificial Bee Colony Algorithm (ABC) is used to solve MJQO problem by simulates the foraging behavior of honey bees. Simulate shows the performance of Artificial Bee Colony Algorithm (ABC) and Particle Swarm Optimization (PSO) are compared to computational time and simulation result indicates that the bees algorithm can solve MJQO problem in less amount of time , lower cost and more efficient than Particle Swarm Optimization (PSO). Using experiments to demonstrate the power of our approaches.