Computer Science ›› 2019, Vol. 46 ›› Issue (3): 321-326.doi: 10.11896/j.issn.1002-137X.2019.03.047

• Interdiscipline & Frontier • Previous Articles     Next Articles

Hierarchical Performance Diagnosis Method for Cloud Operating System

YUAN Yue   

  1. School of Information,Renmin University of China,Beijing 100872,China
  • Received:2018-09-30 Revised:2018-12-28 Online:2019-03-15 Published:2019-03-22

Abstract: Recently,quite some researchers aim to develop automatic performance diagnostic tools for dealing with the large-scale and high-load distributed environment.Cloud operating system is the middle layer between cloud user and cloud resource,and diagnosing and settling the problem of slow response of cloud operating system is helpful for optimizing the performance of cloud computing system.It is a challenging job to analyze the performance of executing task in large-scale and complex distributed cloud computing environment.In light of this,this paper proposed a log-based performance diagnosis method for cloud operating system to find out the reason for low execution speed of appointed tasks and provide clues for performance optimization.This method combines the implementation principal of cloud operating system,separates and extracts relevant logs of each executing tasks from the massive logs generated by cloud operating system,and extracts key information,so as to construct hierarchical performance description model and refine the analysis granularity to function executed granularity layer by layer.Finally,through using this method,the main factor of low execution speed can be gotten,which can assist to locate the source of abnormal performance,and it doesn’t need to modify the source code and use the source code to conduct analysis.This paper utilized the OpenStack as prototype system,created the cloud computing environment,and conducted large-scale concurrent simulation experiment.The experimental results demonstrate that the proposed method can provide efficient clues for optimizing system performance and improve the performance obviously,e.g. the consumed time of cloud resource scheduling can be reduced from minute level to second level.

Key words: Cloud computing, IaaS, Log analysis, System performance diagnosis

CLC Number: 

  • TP311
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