Database Query Optimization based on Hybrid Variable Particle Swarm Optimization Algorithm
Query optimization is a Key research topic in the database research area aiming at solving the problem of premature convergence and local optimal trap in the traditional particle swarm optimization algorithm,this Paper Proposed a novel database query optimization algorithm called Hybrid Variable Particle Swarm Optimization (HV-PSO); Firstly,database query optimization mathematical model is established,then the optimal solution is found by using information transferring and sharing mechanism of particles.This research has two novelties which contribute to the literature: 1.Dynamic charge of particle inertia weight in the optimization process to accelerate the convergence; 2.The introduction of ”hybrid” variation operator to increase the diversity of population.Finally,the simulation experiments are carried out to test the performance of HV-PSO.The results show that the HV-PSO could solve the deficiency of the traditional Particle swarm optimization algorithm,not only improving the database query efficiency,but also obtaining better query plan.Especially,it has predominant advantage for querying large relational connections.
Database query Particle swarm optimization algorithm Dynamic inertial weigh Multi-Joint Query Hybrid mutation Query plan
Fen CHEN Yan TANG Fan-Ping ZHANG
Suqian College Department of Computer Science,Suqian,Jiangsu,China Computer and Information Engineering,Hohai University,Nanjing,Jiangsu,Chian College of Water Conservancy and Hydropower Engineering,Hohai University,Jiangsu,China
国内会议
杭州
英文
1-7
2014-10-18（万方平台首次上网日期，不代表论文的发表时间）