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| 面向云环境的自适应集群调整方法 | |
| 引用本文： | 周欢云,王伟,张文博.面向云环境的自适应集群调整方法[J].计算机科学与探索,2011,5(4):347-355. |
| 作者姓名： | 周欢云 王伟 张文博 |
| 作者单位： | 1. 中国科学院,软件研究所软件工程技术中心,北京,100190;中国科学院,研究生院,北京,100190 2. 中国科学院,软件研究所软件工程技术中心,北京,100190;中国科学院,软件研究所,计算机科学重点实验室,北京,100190 3. 中国科学院,软件研究所软件工程技术中心,北京,100190 |
| 基金项目： | The National Grand Basic Research 973 Program of China under Grant No.2009CB320704 (国家重点基础研究发展规划，the National High-Tech Research and Development Plan of China under Grant No.2007AA010301 (国家高技术研究发展计划，the National Science and Technology Major Special Projects High-Nuclear-Based Project of China under Grant No.2009ZX01043-002-003 |
| 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 |
| 修稿时间： | |
Self-adaptive Adjusting Approach for Cluster in Cloud Computing |
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| ZHOU Huanyun,WANG Wei,ZHANG Wenbo.Self-adaptive Adjusting Approach for Cluster in Cloud Computing[J].Journal of Frontier of Computer Science and Technology,2011,5(4):347-355. | |
| Authors: | ZHOU Huanyun WANG Wei ZHANG Wenbo |
| Affiliation: | 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 |
| 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. |
| Keywords: | cloud computing self-adaptive cluster load balancing performance diagnosis |
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