基于组件服务质量和服务性能的云服务性能瓶颈诊断方法

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清华大学辅仁网/2017-07-07

郭军, 马安香, 闫永明, 孟煜, 张斌

东北大学计算机科学与工程学院, 沈阳 110819

Cloud service performance bottleneck diagnosis based on the component service quality and performance

GUO Jun, MA Anxiang, YAN Yongming, MENG Yu, ZHANG Bin

School of Computer Science and Engineering, Northeastern University, Shenyang 110819, China

摘要:

输出: BibTeX | EndNote (RIS)

摘要瓶颈组件服务的诊断是保障面向服务业务流程的云服务系统性能的关键环节。传统诊断方法是通过评估组件服务的最大运行时延来确定导致整个组合服务质量变差的组件服务，未考虑组件服务的重要性，影响判断的准确性。该文在分析了各个组件服务质量的基础上，综合评估组件服务质量和重要性，提出了一种基于组件服务质量和服务性能的云服务性能瓶颈诊断方法，用来确定云服务瓶颈组件服务。仿真实验的结果验证了该瓶颈诊断方法的有效性和准确性。

关键词 ：云服务,组件,瓶颈诊断,服务质量,服务性能

Abstract：Bottlenecks in component services need to be identified to ensure the performance of cloud service system-oriented service business processes. Traditional approaches for evaluating component service bottlenecks often evaluate the maximum run time delay in the component services to determine the cause of the quality-of-service deterioration. However, these approaches do not consider the importance of the component services, which influences the evaluation accuracy. A cloud service bottleneck diagnostic method is given here based on the quality of service on the various components in the analysis for comprehensive assessments of the quality of service and the component importance to identify cloud service bottlenecks in component services. Simulations show the effectiveness and accuracy of this bottleneck diagnosis method.

Key words：cloud services component bottleneck diagnosis service quality service performance

收稿日期: 2016-07-01 出版日期: 2017-02-21

ZTFLH:

TP311.5

引用本文:

郭军, 马安香, 闫永明, 孟煜, 张斌. 基于组件服务质量和服务性能的云服务性能瓶颈诊断方法[J]. 清华大学学报（自然科学版）, 2017, 57(2): 208-212.
GUO Jun, MA Anxiang, YAN Yongming, MENG Yu, ZHANG Bin. Cloud service performance bottleneck diagnosis based on the component service quality and performance. Journal of Tsinghua University(Science and Technology), 2017, 57(2): 208-212.

链接本文:

http://jst.tsinghuajournals.com/CN/10.16511/j.cnki.qhdxxb.2017.22.016或 http://jst.tsinghuajournals.com/CN/Y2017/V57/I2/208

图表:

图1 瓶颈诊断基本过程

表1 组件服务相关参数符号

图2 组件服务调用关系

图3 基于组件服务质量和重要性的性能瓶颈诊断算法

表2 组件服务调用数量表

图4 增量部署两种组件服务副本的效果对比

图5 响应时间随副本个数变化

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