In order to better solve the problem of distributed query optimization, a query optimization algorithm on gene expression programming （GEP） （QO-GEP） is presented. On the basis of QO-GEP, distributed GEP query opti...In order to better solve the problem of distributed query optimization, a query optimization algorithm on gene expression programming （GEP） （QO-GEP） is presented. On the basis of QO-GEP, distributed GEP query optimization on grid service （DGEPQO-GS） is proposed which combines grid service. Simulated experiments show that with the increment of the number of query relation, query time which QO-GEP carries out query decreases apparently. Meanwhile, with the increase of the number of grid nodes, the average querying success rate of DGEPQO-GS increases significantly.展开更多
基金supported by the National Natural Science Foundation of China (60973139, 60773041)the Natural Science Foundation of Jiangsu Province (BK2008451)+5 种基金Special Fund for Software Technology of Jiangsu ProvinceSpecial Fund for the Development of Modern Service Industry of Jiangsu ProvinceFund of Jiangsu Provincial Key Laboratory for Computer Information Processing TechnologyPostdoctoral Foundation (0801019C, 20090451240, 20090451241)Science & Technology Innovation Fund for higher education institutions of Jiangsu Province (CX09B_153Z, CX08B_086Z)the six kinds of Top Talent of Jiangsu Province (2008118)
文摘In order to better solve the problem of distributed query optimization, a query optimization algorithm on gene expression programming （GEP） （QO-GEP） is presented. On the basis of QO-GEP, distributed GEP query optimization on grid service （DGEPQO-GS） is proposed which combines grid service. Simulated experiments show that with the increment of the number of query relation, query time which QO-GEP carries out query decreases apparently. Meanwhile, with the increase of the number of grid nodes, the average querying success rate of DGEPQO-GS increases significantly.
