| 云环境下基于改进遗传算法的虚拟机调度策略 |
| |
| 引用本文： | 袁爱平,万灿军.云环境下基于改进遗传算法的虚拟机调度策略[J].计算机应用,2014,34(2):357-359. |
| |
| 作者姓名： | 袁爱平 万灿军 |
| |
| 作者单位： | 1. 长沙民政职业技术学院 软件学院，长沙 410004；2. 湖南大学 计算机与通信学院，长沙 410082 |
| |
| 基金项目： | 湖南省教育规划基金项目;湖南省科技计划项目 |
| |
| 摘 要： | 针对云环境下服务器内部多种资源间分配不均衡问题，提出了一种多维资源协同聚合的虚拟机调度算法MCCA。该算法在分组遗传算法的基础上，采用模糊逻辑及基于资源利用率多维方差的控制参量，设计适应度函数指导搜索解空间。算法使用基于轮盘赌法的选择方法，并对交叉和变异等进行了优化，以实现快速有效地获取近似最优解。在CloudSim环境下进行了仿真，实验结果表明该算法对均衡多维资源分配和提高资源综合利用率具有一定的优势。
|
| 关 键 词： | 云计算 虚拟机 多维均衡 分组遗传算法 |
| 收稿时间： | 2013-08-21 |
| 修稿时间： | 2013-10-17 |
Virtual machine deployment strategy based on improved genetic algorithm in cloud computing environment |
| |
| YUAN Aiping WAN Chanjun.Virtual machine deployment strategy based on improved genetic algorithm in cloud computing environment[J].journal of Computer Applications,2014,34(2):357-359. |
| |
| Authors: | YUAN Aiping WAN Chanjun |
| |
| Affiliation: | 1. Department of Software, Changsha Social Work College, Changsha Hunan 410004, China；2. School of Computer and Communication, Hunan University, Changsha Hunan 410082, China |
| |
| Abstract: | Aiming at improving the resource utilization of data center by balanced usage of multiple resources, a scheduling algorithm based on group genetic algorithm for multi-dimensional resources coordination was proposed to solve the virtual machine deployment problem. To guide the solution searching, a fuzzy logic based multi-dimensional fitness function was raised. Meanwhile, innovative optimization of crossover and mutation was put forward to improve the solution quality. The results of simulation in CloudSim environment prove that using the proposed algorithm can obtain better multi-dimensional resources performance and higher resource utilization rate. |
| |
| Keywords: | cloud computing virtual machine multi-dimensional balancing group genetic algorithm |
| 本文献已被 CNKI 等数据库收录！ |
| 点击此处可从《计算机应用》浏览原始摘要信息 |
|
点击此处可从《计算机应用》下载全文 |
