计算机科学 ›› 2022, Vol. 49 ›› Issue (2): 353-367.doi: 10.11896/jsjkx.201100140

• 计算机网络 • 上一篇    下一篇

基于BP神经网络的智能云效能模型

夏静, 马中, 戴新发, 胡哲琨   

  1. 武汉数字工程研究所 武汉430205
  • 收稿日期:2020-11-20 修回日期:2021-01-19 出版日期:2022-02-15 发布日期:2022-02-23
  • 通讯作者: 夏静(673718032@qq.com)
  • 基金资助:
    热能动力技术重点实验室开放基金资助项目(TPL2019C01)

Efficiency Model of Intelligent Cloud Based on BP Neural Network

XIA Jing, MA Zhong, DAI Xin-fa, HU Zhe-kun   

  1. Wuhan Digital Engineering Institute,Wuhan 430205,China
  • Received:2020-11-20 Revised:2021-01-19 Online:2022-02-15 Published:2022-02-23
  • About author:XIA Jing,born in 1982,Ph.D.Her main research interests include virtualization technology,intelligent computing and intelligent cloud.
  • Supported by:
    Open Fund of Key Laboratory of Thermal Power Technology(TPL2019C01).

摘要: 面对日趋庞大和复杂的智能应用,建立有效的云服务质量模型是评价云服务质量的重要手段。然而,由于智能云各层资源的多样性、动态性等特点,智能云服务效能的评估具有很大的难度。针对目前智能云计算领域缺乏标准和统一的云服务质量评价指标和云服务建模手段的问题,文中将智能云抽象的服务质量具体化为云服务效能,云服务效能被定义为反映云服务能力水平的服务可用性、可靠性,以及体现服务效率的性能,即通过云服务效能输出定量的评价智能云的整体服务能力水平。并且提出了一种基于BP神经网络的智能云效能模型,通过BP神经网络模拟智能云服务的输入特征与服务效能之间复杂的非线性关系,一旦确定输入特征,即可预测输出的服务效能评价指标,这就要求效能模型能够实时并准确地根据系统配置输入特征,预测当前系统的服务能力。实验结果表明,BP神经网络模型作为智能云服务效能模型的建模工具,具有较好的计算效率和准确率。

关键词: BP神经网络, 服务效能, 输入特征, 效能模型, 智能云

Abstract: Recently,we are facing the increasingly large and complex intelligent applications in cloud computing.Establishing an effective quality model of cloud service is an important methodology to evaluate cloud service quality.However,due to the diversity and dynamic characteristics of intelligent cloud resources,it is very difficult to evaluate the service efficiency of intelligent cloud.At present,there is a lack of standard and unified cloud service quality evaluation and cloud service model in the field of intelligent cloud computing.In this paper,the abstract service quality of intelligent cloud is embodied as cloud service efficiency,and cloud service efficiency is defined as the service availability,reliability and performance reflecting service efficiency.That is to quantitatively evaluate the overall service capability of intelligent cloud through the output of cloud service efficiency.Moreover,this paper proposes an efficiency model of intelligent cloud based on BP neural network.The complex nonlinear relationship between input characteristics and output service efficiency of intelligent cloud is simulated by BP neural network.Once the input characteristics are determined,the output service efficiency can be computed.The efficiency model is responsible for predicting the service level of the current system in real time according to the input characteristics of the system accurately.The experimental results show that the BP neural network model,as a modeling tool of service efficiency model,has good computing efficiency and accuracy.

Key words: BP neural network, Efficiency model, Input characteristics, Intelligent cloud, Service efficiency

中图分类号: 

  • TP183
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