Multi-Join Query Optimization in Distributed Database Based on Genetic Algorithm
As the data capacity extending of the distributed database, the problem of multi-join query optimization largely influence the efficiency of the data queries. The main content of this thesis is to improve the genetic algorithm based on coded tree. The thesis put forward a new mutation operator, which can solve the problem that crossover operators capability of generating new offspring is not better. Results obtained by the authors experiment show that we get a set of appropriate values of genetic algorithms parameters, and use the values to process multi-join queries. Simulator confirmed the improved algorithm is more efficient for query optimization than before.
Jing Zhu Lin Du
School of Computer,China University of Geosciences, Wuhan, China.430030 School of Computer .China University of Geosciences, Wuhan, China 430030
国际会议
武汉
英文
188-190
2008-12-19（万方平台首次上网日期，不代表论文的发表时间）