Cloud database dynamic route query based on self-adaptive ant colony optimization

doi:10.3778/j.issn.1002-8331.2010.09.004

Computer Engineering and Applications ›› 2010, Vol. 46 ›› Issue (9): 10-12.DOI: 10.3778/j.issn.1002-8331.2010.09.004

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Cloud database dynamic route query based on self-adaptive ant colony optimization

SHI Heng-liang^1，2，3，REN Chong-guang^1，3，BAI Guang-yi^1，3，PU Jie-xin²

1.School of Computer Science，Nanjing University of Science and Technology，Nanjing 210094，China
2.School of Electronic Information，Henan University of Science & Technology，Luoyang，Henan 471003，China
3.Noah IT Solution Com.，LTD，Suzhou，Jiangsu 215021，China

Received:2009-12-30 Revised:2010-02-10 Online:2010-03-21 Published:2010-03-21
Contact: SHI Heng-liang

自适应蚁群优化的云数据库动态路径查询

史恒亮^1，2，3，任崇广^1，3，白光一^1，3，普杰信²

1.南京理工大学计算机学院，南京 210094
2.河南科技大学电信学院，河南洛阳 471003
3.方舟信息技术（苏州）有限公司，江苏苏州 215021

通讯作者: 史恒亮

Abstract

Abstract: Although ACO（Ant Colony Optimization） algorithm has strong advantages in treating dynamical optimal route query problem，pheromone volatility factor’s static setting brings unstable convergence speed and traps into local optimization answer problems，especially for cloud database.Combining ACO algorithm and cloud database，this paper proposes a novel pheromone volatility self-adaptive algorithm which can find the requiring database rapidly and effectively，and reduce the dynamic routing burdens of cloud database routing，and enhance the efficiency of cloud computing to a large extent.

Key words: self-adaptive, pheromone, Ant Colony Optimization（ACO）, cloud database, dynamic routing query

摘要： 蚁群算法对于解决动态最优路径查询问题具有很强的优势，但蚁群算法中的信息素挥发因子的静态设置容易带来收敛速度不稳定和陷入局部最优解的问题，在云数据库中更是明显。融合了蚁群算法和云数据库，并提出了信息素挥发因子自适应的算法，该算法能够在云中快速、合理地找到所需访问的数据库，减少了云数据库数路由的动态负荷，从而很大程度上提高云计算的效率。

关键词: 自适应, 信息素, 蚁群算法, 云数据库, 动态路径查询

CLC Number:

TP311

SHI Heng-liang^1，2，3，REN Chong-guang^1，3，BAI Guang-yi^1，3，PU Jie-xin². Cloud database dynamic route query based on self-adaptive ant colony optimization[J]. Computer Engineering and Applications, 2010, 46(9): 10-12.

史恒亮^1，2，3，任崇广^1，3，白光一^1，3，普杰信². 自适应蚁群优化的云数据库动态路径查询[J]. 计算机工程与应用, 2010, 46(9): 10-12.

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Cloud database dynamic route query based on self-adaptive ant colony optimization

自适应蚁群优化的云数据库动态路径查询

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