Database Query Optimization Based on Parallel Ant Colony Algorithm

Abstract

Multi-join query optimization is an important technique for designing and implementing database manage system. It is a crucial factor that affects the capability of database. This paper proposes a new algorithm to solve the problem of multi-join query optimization based on parallel ant colony optimization. In this paper, details of the algorithm used to solve multi-join query optimization problem have been interpreted, including how to define heuristic information, how to implement local pheromone update and global pheromone update and how to design state transition rule. After repeated iteration, a reasonable solution is obtained. Compared with genetic algorithm, the simulation result indicates that parallel ant colony optimization is more effective and efficient.