| 云环境下机群弹性负载均衡机制 |
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| 引用本文： | 杜垚,郭涛,陈俊杰.云环境下机群弹性负载均衡机制[J].计算机应用,2013,33(3):830-833. |
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| 作者姓名： | 杜垚 郭涛 陈俊杰 |
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| 作者单位： | 1.太原理工大学 计算机科学与技术学院, 太原 030024;
2.太原理工大学 信息中心, 太原 030024 |
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| 基金项目： | 山西省科技基础条件平台建设项目(2010091103-0101); 山西省研究生优秀创新项目(20103031); 太原理工大学2012年校专项青年基金资助项目(2012L092)。 |
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| 摘 要： | 为克服传统刚性负载均衡机制不能适应多变的网络环境的缺陷,解决云环境下已有负载均衡机制存在不能充分利用弹性机制,且服务质量(QoS)不稳定的问题,提出一种基于绿色计算资源池策略的云环境弹性负载均衡机制,根据系统资源利用率对负载进行量化,量化结果决定资源池虚拟机的分配,最后结合虚拟机的使用情况,回收资源,提高资源的利用率。实验结果显示在该负载均衡机制下,响应时间稳定在2.5s左右,整体服务质量有明显提高,降低了电能消耗,验证了该机制的有效性。
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| 关 键 词： | 云计算 虚拟机 服务质量 负载均衡 绿色计算 |
| 收稿时间： | 2012-09-24 |
| 修稿时间： | 2012-10-31 |
Fleet elastic load balancing mechanism in cloud environment |
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| DU Yao GUO Tao CHEN Junjie.Fleet elastic load balancing mechanism in cloud environment[J].journal of Computer Applications,2013,33(3):830-833. |
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| Authors: | DU Yao GUO Tao CHEN Junjie |
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| Affiliation: | 1.College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan Shanxi 030024, China;
2.Center of Information, Taiyuan University of Technology, Taiyuan Shanxi 030024, China |
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| Abstract: | In order to overcome the defects of traditional rigid load balancing mechanism that it can not adapt to changing network environment, and to solve the problem of load balancing mechanisms in cloud environment that it can not take full advantage of elastic characteristics and Quality of Service (QoS) would be unstable, this paper proposed a new load balancing mechanism in cloud environment based on green computing resource pool strategy. It quantified the load according to the utilization rate of system resources and the quantization decided distribution of virtual machines. On the basis of the use of the virtual machines, resources would be recycled to improve resource utilization. The experimental results show that the response time stablizes around 2.5 seconds, the overall QoS has been obviously improved with the power consumption reduced, and the effectiveness of the mechanisms has been verified. |
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| Keywords: | cloud computing virtual machine Quality of Service (QoS) load balancing green computing |
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