Cloud database dynamic route scheduling based on polymorphic ant colony optimization algorithm
Chen Qing, Yong Zhong, Liuming Xiang
COMPUTER MODELLING & NEW TECHNOLOGIES 2014 18(2) 161-165
Chengdu Inst. of Computer Applications, Chinese Academy of Science, People's South Road, Section 4 Chengdu, China
Big Data era spawned the development of Cloud database. As a database, which need easily scale out, how to quickly find the available nodes are focuses of the study. Ant colony algorithm is based on bionic optimization algorithm and has the characters of smart searching, global optimization, robustness, distributed computing and easily combined with other algorithms, but the algorithm is prone to premature convergence, making the results often caught local optimum. According to this, polymorphic ant colony algorithm was proposed which combined with a Cloud database; the algorithm can quickly and reasonably find the nodes in Cloud environment, reducing the load of routing, thus greatly improved the Cloud database’s ability of scaling out.