《计算机应用研究》|Application Research of Computers

基于分布估计蛙跳算法的云资源调度方法

Cloud resource scheduling method based on estimation of distribution shuffled frog leaping algorithm

免费全文下载 (已被下载 次)  
获取PDF全文
作者 张恒巍,卫波,王晋东,何嘉婧
机构 解放军信息工程大学,郑州 450001
统计 摘要被查看 次,已被下载
文章编号 1001-3695(2014)11-3225-04
DOI 10.3969/j.issn.1001-3695.2014.11.006
摘要 针对云计算环境中的资源调度很少同时兼顾最短完成时间和最低服务成本的问题,设计能够综合反映时间和成本的适应度函数,在此基础上提出了基于分布估计蛙跳算法的云资源调度方法。结合遗传算法的交叉操作重新定义蛙跳算法的进化算子,使其适用于整数编码的调度问题;引入分布估计进化策略,突破了标准蛙跳算法搜索模式的局限,使算法具有更全面的学习能力。仿真实验结果表明,在云资源调度问题的求解中,该算法的收敛性能和寻优能力均优于标准的蛙跳算法和分布估计算法。
关键词 云计算;资源调度;蛙跳算法;分布估计算法;交叉操作;概率模型
基金项目 国家自然科学基金资助项目(61303074,61309013)
河南省科技攻关计划资助项目(12210231003,13210231002)
本文URL http://www.arocmag.com/article/01-2014-11-006.html
英文标题 Cloud resource scheduling method based on estimation of distribution shuffled frog leaping algorithm
作者英文名 ZHANG Heng-wei, WEI Bo, WANG Jin-dong, HE Jia-jing
机构英文名 PLA Information Engineering University, Zhengzhou 450001, Chian
英文摘要 Focusing on the problem of high efficiency resource scheduling in cloud computing environment, since current resource scheduling algorithm had been less given consideration to the shortest completion time and the least cost of the services, this paper designed the fitness function which could comprehensive response the time and cost, and proposed an estimation of distribution-shuffled frog leaping algorithm (EDSFLA).This algorithm redefined the evolutional operators of shuffled frog leaping algorithm (SFLA), utilizing the cross operators of genetic algorithm, targeted in applying to scheduling problem with integer-coded. EDSFLA introduced evolutionary strategy of estimation of distribution to break the confine of search pattern in the standard SFLA, and made the learning ability of this algorithm more comprehensive. Experimental results show that this algorithm has more capability in convergence and searching ability compared with the standard SFLA and EDA in solving cloud resource scheduling problems.
英文关键词 cloud computing; resource scheduling; shuffled frog leaping algorithm; estimation of distribution algorithm; crossover operation; probabilistic model
参考文献 查看稿件参考文献
  [1] BUYYA R, YEO C S, VENUGOPAL S, et al. Cloud computing and emerging IT platforms:vision, hype, and reality for delivering computing as the 5th utility[J] . Future Generation Computer Systems, 2009, 25(6):599-616.
[2] ARMBRUST M, FOX A, GRIFFITH R, et al. A view of cloud computing[J] . Communications of the ACM, 2010, 53(4):50-58.
[3] 罗军舟, 金嘉晖, 宋爱波, 等. 云计算:体系架构与关键技术[J] . 通信学报, 2011, 32(7):3-21.
[4] 刘卫宁, 靳洪兵, 刘波. 基于改进量子遗传算法的云计算资源调度[J] . 计算机应用, 2013, 33(8):2151-2153.
[5] 王波, 张晓磊. 基于粒子群遗传算法的云计算任务调度研究[J/0L] . 计算机工程与应用, (2013-09-04). http://www. cnki. net/kcms/detail/11. 2127. TP. 20130904. 1341. 006. html .
[6] TAYAL S, SINGH G G. Tasks scheduling optimization for the cloud computing system[J] . International Journal of Advanced Engineering Sciences and Technologies, 2011, 5(2):11- 15.
[7] FANG Yi-qiu, WANG Fei, GE Jun-wei. A task scheduling algorithm based on load balancing in cloud computing[C] // Proc of the 2nd International Conference on Web Information Systems and Mining. Berlin:Springer-Verlag, 2010:271-277.
[8] 孙大为, 常桂然, 李凤云, 等. 一种基于免疫克隆的偏好多维QoS云资源调度优化算法[J] . 电子学报, 2011, 39(8):1824- 1831.
[9] EUSUFF M M, LANSEY K E. Water distribution network design using the shuffled frog leaping algorithm[C] // Proc of Word Water Congress. 2004:111.
[10] XU Ye, WANG Ling, ZHOU Gang, et al. An effective shuffled frog leaping algorithm for solving hybrid flow-shop scheduling problem[C] // Proc of the 7th International Conference on Advanced Intelligent Computing. Berlin:Springer-Verlag, 2011:560-567.
[11] 郑仕链, 楼才义, 杨小牛. 基于改进混合蛙跳算法的认知无线电协作频谱感知[J] . 物理学报, 2010, 59(5):3611- 3617.
[12] 周树德, 孙增圻. 分布估计算法综述[J] . 自动化学报, 2007, 33(2):113- 124.
[13] MUHLENBEIN H. The equation for response to selection and its use for prediction[J] . Evolutionary Computation, 1997, 5(3):303- 346.
[14] BALUJA S, CARUANA R. Removing the genetics from standard genetic algorithm[C] //Proc of International Conference on Machine Learning. San Francisco:Morgan Kaufmann Publisher, 1995:38- 46.
[15] The Cloud Lab. CloudSim[EB/OL] . (2011-08-15). http://www. cloudbus. org/cloudsim.
收稿日期 2013/11/21
修回日期 2014/1/3
页码 3225-3228,3233
中图分类号 TP181
文献标志码 A