基于包簇映射的云计算资源分配框架

doi:10.11772/j.issn.1001-9081.2016.10.2704

计算机应用 ›› 2016, Vol. 36 ›› Issue (10): 2704-2709.DOI: 10.11772/j.issn.1001-9081.2016.10.2704

基于包簇映射的云计算资源分配框架

卢浩洋¹, 陈世平^1,2

1. 上海理工大学光电信息与计算机工程学院, 上海 200093;
2. 上海理工大学信息化办公室, 上海 200093

收稿日期:2016-04-15 修回日期:2016-05-30 出版日期:2016-10-10 发布日期:2016-10-10
通讯作者: 卢浩洋,E-mail:1412201648@qq.com
作者简介:卢浩洋(1991—),男,江苏盐城人,硕士,主要研究方向:计算机网络、云计算;陈世平(1964—),男,浙江绍兴人,教授,博士生导师,博士,主要研究方向:计算机网络、云计算、分布式计算。
基金资助:
国家自然科学基金资助项目（61472256）；上海市教委科研创新重点项目（12zz137）；上海市一流学科建设项目（S1201YLXK）。

Resource allocation framework based on cloud computing package cluster mapping

LU Haoyang¹, CHEN Shiping^1,2

1. School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China;
2. Network and Information Center Office, University of Shanghai for Science and Technology, Shanghai 200093

Received:2016-04-15 Revised:2016-05-30 Online:2016-10-10 Published:2016-10-10
Supported by:
BackgroundThis work is partially supported by the National Natural Science Foundation of China (61472256), the Scientific Research and Innovation Key Project of Shanghai Municipal Education Commission (12zz137), the Shanghai First Class Discipline Construction Project (S1201YLXK).

摘要/Abstract

摘要： 在云计算资源调度中存在着结构复杂、数据量庞大的可扩展问题，针对该问题提出了一种基于包簇映射的资源管理框架。该框架下包内允许资源共享，当指定资源共享使用模式后，资源调配更具灵活性。将改进的基于包的遗传算法运用到该框架中，采用染色体组方式和资源方式进行编码，根据染色体长度变化设计交叉算子和变异算子，将簇的个数与包的资源相互整合，并且通过抽象模型来降解问题规模。实验结果表明，在基于包簇映射框架下的遗传算法与传统的以虚拟机为中心框架下的遗传算法和基于包簇框架的首次适应算法相比，在CPU利用率方面分别平均提高9%和5%，在内存利用率方面分别平均提高14%和7%。实验结果表明，所提出的包簇框架下的遗传算法能有效减少簇节点的使用数量，提高资源利用率。

关键词: 云计算, 资源调度, 包簇, 遗传算法, 包放置

Abstract: Concerning the complex structure and huge amount of data of resource management in cloud computing, a package-cluster mapping based resource management framework was proposed. In this framework, resources are allowed to be shared in a package among virtual machines, and the resource scheduling becomes more flexibly by using a specific resource sharing model. Moreover, an improved package-based Genetic Algorithm (GA) was used in this framework, which encoded package groups with chromosome group and resource pattern, and designed crossover operators and mutation operators according to the change of the chromosome length. The number of clusters and the resources of the packages were integrated, the scale of the problem was solved by using an abstract model. Experimental results showed that, compared with the traditional virtual machine centered framework based genetic algorithm and the package-cluster framework based adaptive algorithm, the CPU utilization of the proposed method was improved by 9% and 5% respectively, and the memory utilization was improved by 14% and 7%, respectively. It proves that the proposed package-cluster mapping framework based algorithm can effectively reduce the number of the used cluster nodes and increase the resource utilization rate.

Key words: cloud computing, resource management, package-cluster, Genetic Algorithm (GA), package placement

中图分类号:

TP393.2

卢浩洋, 陈世平. 基于包簇映射的云计算资源分配框架[J]. 计算机应用, 2016, 36(10): 2704-2709.

LU Haoyang, CHEN Shiping. Resource allocation framework based on cloud computing package cluster mapping[J]. Journal of Computer Applications, 2016, 36(10): 2704-2709.

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基于包簇映射的云计算资源分配框架

Resource allocation framework based on cloud computing package cluster mapping

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