• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

J4 ›› 2014, Vol. 36 ›› Issue (11): 2061-2066.

• 论文 • 上一篇    下一篇

基于时间序列的感知QoS的云服务组合

肖文娟,段玉聪   

  1. (海南大学信息科学技术学院,海南 海口 570228)
  • 收稿日期:2014-06-09 修回日期:2014-08-19 出版日期:2014-11-25 发布日期:2014-11-25
  • 基金资助:

    国家自然科学基金资助项目(61363007);海南大学资助项目(HDSF201310,kyqd1242)

QoS-aware cloud service composition based on time series             

XIAO Wenjuan,DUAN Yucong   

  1. (College of Information Science and Technology,Hainan University,Haikou 570228,China)
  • Received:2014-06-09 Revised:2014-08-19 Online:2014-11-25 Published:2014-11-25

摘要:

研究基于时间序列的感知QoS的云服务组合,将服务的QoS偏好随时间不断变化的过程纳入云服务组合的研究范围,将云服务组合建模成时间序列的相似度对比问题。分别用欧几里得距离和扩展Frobenius范数距离度量二维时间序列的相似度,继而用基于主成分分析的扩展Frobenius范数距离和欧几里得距离、BruteForce等方法度量多维时间序列的相似度,通过实验对比验证扩展Frobenius范数距离度量相似度在时间和准确性上的优越性。关

关键词: 时间序列, QoS, 云服务组合, 相似度对比

Abstract:

In this paper, we study QoS-aware cloud service composition based on time series, taking the sustaining change process of service QoS preference into research scope of cloud service composition,and transform the composition of cloud services into similarity comparison problems between time series.Euclidean distance and the extend Frobenius norm distance are used to measure similarity between two-dimensional time series respectively. In the next,the extend Frobenius norm distance or Euclidean distance based on principal component analysis and BruteForce method are adopted to measure the similarity between multidimensional time series. Experiments show that the extend Frobenius norm distance has better performance on similarity measurement in time and accuracy.

Key words: time series;QoS;cloud service composition;similarity comparison