Method for classifying operated load in virtual machine under cloud computing environment

A cloud computing environment and classification method technology, applied in the field of load classification, can solve problems such as large amount of resources consumed, poor accuracy, and failure to meet system requirements, achieve high load classification accuracy, and avoid excessive training sets. , the effect of avoiding performance loss

Active Publication Date: 2013-09-04
ZHEJIANG UNIV
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  • Abstract
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

First of all, traditional decision tree classification, Bayesian classification, neural network algorithm, KNN and other machine learning classification algorithms are sensitive to the data dimension of the training set and test set. When the monitoring data dimension reaches 21 dimensions, the calculation time It is very long and consumes a lot of resources, which does not meet the requirements of the system
The SVM (Support Vector Machine) classification method is not sensitive to dimensions, but the accuracy of classification in this environment is not good, and the requirements for the training set are too strict

Method used

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  • Method for classifying operated load in virtual machine under cloud computing environment
  • Method for classifying operated load in virtual machine under cloud computing environment
  • Method for classifying operated load in virtual machine under cloud computing environment

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Embodiment 1

[0031] The present invention is a method for classifying loads running on a virtual machine in a cloud computing environment, and the method is designed figure 1 The process structure mainly includes:

[0032] Data collector: monitoring system runtime status, used for parameter collection of 21-dimensional monitoring data.

[0033] Data preprocessor: Complete the preprocessing of the acquired monitoring data, that is, normalize the acquired monitoring data to [0,1], to ensure that the impact will not be unbalanced due to the large difference in data values.

[0034] TSRSVM classifier: Classify the preprocessed monitoring data through the TSRSVM classifier, and each monitoring data vector will be classified into one of CPU-intensive, memory-intensive, I / O-intensive and network-intensive.

[0035] Optimal decision maker: make statistics on the monitoring data vectors classified by the TSRSVM classifier, and judge the type of attachment in this time period according to the stati...

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Abstract

The invention discloses a method for classifying operated load in a virtual machine under cloud computing environment. The method includes firstly acquiring monitoring parameters in 5 minutes of load operation and subjecting the monitored parameters to normalization processing; classifying load monitored into four categories such as CPU (central processing unit)-intensive load, memory intensive load, I/O (input/output) intensive load and network intensive load by means of TSRSVM (training sets refresh SVM); providing corresponding customized optimizing strategies for operation systems which running the four categories of intensive loads, and monitoring operating state of the systems through a performance comparison device; indicating that classification strategies are correct if performance of the systems is improved, otherwise, indicating that the classification strategies are incorrect. By the method, accuracy of load classification is high and system performance loss is low.

Description

technical field [0001] The invention relates to a load classification method running on a virtual machine in a cloud computing environment. Background technique [0002] With the rapid development of cloud computing technology represented by virtualization technology, more and more enterprises begin to use cloud computing system to improve system operation efficiency and management efficiency. The cloud computing platform shields virtual machines from the underlying hardware details, and different types of virtual machines can run on physical servers in the cloud system at the same time. At the same time, cloud computing also has the characteristics of dynamic contraction of virtual machine supply and efficient integration of server resources. This makes cloud computing a research hotspot. In the cloud computing environment, resources are obtained on demand, and the traditional virtual machine operating system achieves global adaptability to all types of applications, resul...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F9/50G06F9/455H04L29/08
Inventor 尹建伟赵新奎李莹邓水光吴健吴朝晖
Owner ZHEJIANG UNIV
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