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CPU (Central Processing Unit) resource utilization forecasting method of fine grit under virtual environment

A CPU resource and virtual environment technology, applied in the field of fine-grained CPU resource usage prediction in virtual environment, can solve problems such as extra CPU consumption, high L2 cache failure rate and instruction interruption, and resource consumption without considering virtualization technology

Active Publication Date: 2013-06-12
ZHEJIANG UNIV
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AI Technical Summary

Problems solved by technology

[0007] 3) The resource consumption generated by virtualization technology is not considered
However, in a cloud environment, the use of virtual technology requires additional resources
Related studies have found that competition between virtual machines (VMs) will lead to additional CPU consumption, higher L2 cache miss rate and instruction interruption

Method used

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  • CPU (Central Processing Unit) resource utilization forecasting method of fine grit under virtual environment
  • CPU (Central Processing Unit) resource utilization forecasting method of fine grit under virtual environment
  • CPU (Central Processing Unit) resource utilization forecasting method of fine grit under virtual environment

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Embodiment Construction

[0043] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0044] Overall realization steps of the present invention are as figure 1 As shown, there are three steps including the extra CPU consumption prediction scheduled by the virtual machine manager, the CPU usage probability density function prediction method for non-bursty loads, and the CPU usage probability density function prediction method for bursty loads. The specific description is as follows :

[0045] In step 1, consider additional CPU consumption forecasts scheduled by the hypervisor. In a virtual environment, the CPU utilization U of each virtual machine is determined by the application system U app , operating system U os and Virtual Machine Manager (VMM) schedule U vm It consists of three parts:

[0046] U=U app + U os + U vm . Formula 1)

[0047] Among them, U app Determined by the load of the application system, U os ca...

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Abstract

The invention discloses a CPU (Central Processing Unit) resource utilization forecasting method of a fine grit under a virtual environment. The method is characterized in that on the basis of difference of CPU use ratios collected by two system performance monitoring tools of Xenmon and Sar, a statistical learning method is adopted to provide an extra CPU consumption forecasting model controlled by a virtual machine manager. On the basis, corresponding CPU use probability density function forecasting methods are provided aiming at two different load characteristics of burstiness and non-burstiness. The CPU resource utilization forecasting method of the fine grit provides a good basis for system resource optimum allocation.

Description

technical field [0001] The invention relates to a fine-grained CPU resource usage prediction method in a virtual environment. Background technique [0002] With the continuous expansion of computing scale, many enterprises and data centers have experienced the phenomenon of server sprawl, that is, the number of servers continues to increase, but the average utilization rate of resources is too low. Relevant surveys show that the resource utilization rate of servers in most enterprises and data centers is only between 5% and 20%. Cloud computing can use virtualization technology to close some idle servers through virtual machine migration and consolidation, so as to solve the problem of server sprawl. In order to realize the on-demand allocation of computing resources, it is necessary to provide accurate system resource analysis and prediction methods. [0003] System resource analysis and prediction mainly refers to predicting the demand of the system for various hardware ...

Claims

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Application Information

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IPC IPC(8): G06F9/50G06F9/455
Inventor 尹建伟陈韩玮邓水光孙小华彭勇吴朝晖
Owner ZHEJIANG UNIV
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