计算机科学与探索 ›› 2011, Vol. 5 ›› Issue (4): 347-355.

• 学术研究 • 上一篇    下一篇

面向云环境的自适应集群调整方法

周欢云1,2, 王 伟1,3, 张文博1   

  1. 1. 中国科学院 软件研究所 软件工程技术中心, 北京 100190
    2. 中国科学院 研究生院, 北京 100190
    3. 中国科学院 软件研究所 计算机科学重点实验室, 北京 100190
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2011-04-01 发布日期:2011-04-01

Self-adaptive Adjusting Approach for Cluster in Cloud Computing

ZHOU Huanyun1,2, WANG Wei1,3, ZHANG Wenbo1   

  1. 1. Technology Center of Software Engineering, Institute of Software, Chinese Academy of Sciences, Beijing 100190, China
    2. Graduate University, Chinese Academy of Sciences, Beijing 100190, China
    3. State Key Laboratory of Computer Science, Institute of Software, Chinese Academy of Sciences, Beijing 100190, China
  • Received:1900-01-01 Revised:1900-01-01 Online:2011-04-01 Published:2011-04-01

摘要: 应用服务器集群是平台即服务(platform as a service, PaaS)模式的主要运行环境。针对云环境下动态变化的用户负载和共享、异构的集群环境, 提出一种自适应集群调整方法, 根据集群负载状况实现资源按需供给。该方法建立了PaaS平台的性能分析模型, 并据此提出自适应的资源供给机制和负载均衡机制。实验结果表明, 通过调节集群节点逻辑资源池的大小和集群节点数量, 配合自适应负载均衡方法, 达到了资源按需供给的目的。

关键词: 云计算, 自适应集群, 负载均衡, 性能诊断

Abstract: Application server cluster is the most important runtime environment in platform as a service (PaaS). Based on the dynamic variable load and shared heterogeneous environment in PaaS, this paper brings forward a self-adaptive approach for cluster adjusting in order to provide resource on-demand corresponding to the cluster load. The approach constructs a performance diagnosis model, then provides self-adaptive mechanism for resource provision and load balancing. The experiment shows that the approach can implement resource provision on-demand through adjusting the size of logic resource pool, the number of cluster nodes and self-adaptive load balancing.

Key words: cloud computing, self-adaptive cluster, load balancing, performance diagnosis