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基于Xen虚拟机的内存资源实时监控与按需调整
引用本文:胡耀,肖如良,姜军,韩佳,倪友聪,杜欣,房丽娜.基于Xen虚拟机的内存资源实时监控与按需调整[J].计算机应用,2013,33(1):254-257.
作者姓名:胡耀  肖如良  姜军  韩佳  倪友聪  杜欣  房丽娜
作者单位:1. 福建师范大学 软件学院, 福州 350108 2. 深圳信息职业技术学院 软件学院, 广东 深圳 518172
基金项目:福建省科技计划重大项目(2011H6006)
摘    要:在虚拟计算环境中,难以实时地监控与分配内存资源。针对以上问题,基于Xen虚拟计算环境,提出一种能够实时监控Xen虚拟机内存(VMM)使用情况的XMMC方法并进行了实现。所提方法运用Xen虚拟机提供的超级调用,其不仅能实时地监控虚拟机内存使用情况,而且能实时动态按需分配虚拟机内存。实验结果表明,XMMC方法对虚拟机应用程序造成的性能损失很小,低于5%;能够对客户虚拟机的内存资源占用情况进行实时的监测与按需调整,为多虚拟机的管理提供方便。

关 键 词:Xen  虚拟机内存  实时监控  按需调整  
收稿时间:2012-07-04
修稿时间:2012-08-11

Virtual machine memory of real-time monitoring and adjusting on-demand based on Xen virtual machine
HU Yao,XIAO Ruliang,JIANG Jun,HAN Jia,NI Youcong,DU Xin,FANG Lina.Virtual machine memory of real-time monitoring and adjusting on-demand based on Xen virtual machine[J].journal of Computer Applications,2013,33(1):254-257.
Authors:HU Yao  XIAO Ruliang  JIANG Jun  HAN Jia  NI Youcong  DU Xin  FANG Lina
Affiliation:1. Faculty of Software, Fujian Normal University, Fuzhou Fujian 350108, China
2. Department of Software, Shenzhen Institute of Information Technology, Shenzhen Guangdong 518172, China
Abstract:In a Virtual Machine (VM) computing environment, it is difficult to monitor and allocate the VM's memory in real-time. To overcome these shortcomings, a real-time method of monitoring and adjusting memory for Xen virtual machine called Xen Memory Monitor and Control (XMMC) was proposed and implemented. This method used hypercall of Xen, which could not only real-time monitor the VM's memory usage, but also dynamically real-time allocated the VM's memory by demand. The experimental results show that XMMC only causes a very small performance loss, less than 5%, to VM's applications. It can real-time monitor and adjust on demand VM's memory resource occupations, which provides convenience for the management of multiple virtual machines.
Keywords:Xen                                                                                                                          Virtual Machine Memory (VMM)                                                                                                                          real-time monitoring                                                                                                                          adjusting on-demand
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