计算机科学与探索 ›› 2013, Vol. 7 ›› Issue (3): 218-226.DOI: 10.3778/j.issn.1673-9418.1209009

• 学术研究 • 上一篇    下一篇

基于时间序列分析的Web Service QoS预测方法

华哲邦1,2,李  萌1,2,赵俊峰1,2+,谢  冰1,2   

  1. 1. 北京大学 信息科学技术学院,北京 100871
    2. 高可信软件技术教育部重点实验室,北京 100871
  • 出版日期:2013-03-01 发布日期:2013-03-05

Web Service QoS Prediction Method Based on Time Series Analysis

HUA Zhebang1,2, LI Meng1,2, ZHAO Junfeng1,2+, XIE Bing1,2   

  1. 1. School of Electronics Engineering and Computer Science, Peking University, Beijing 100871, China
    2. Key Laboratory of High Confidence Software Technologies, Ministry of Education, Beijing 100871, China
  • Online:2013-03-01 Published:2013-03-05

摘要: 通过网络提供服务的Web Service的服务质量会随着网络环境、服务器负载等因素的变化而变化,如何更好地帮助用户选择在未来一段时间内符合服务质量需求的Web Service,是目前服务计算领域中需要解决的关键问题之一。针对上述问题,提出了一种基于时间序列分析的Web Service QoS预测方法,并实现了相应的Web Service QoS自动预测工具。该工具能够根据Web Service的历史QoS数据,有效地预测未来短期内的QoS信息。以17 832个Web Service的历史数据为基础,设计了相关实验,并验证了方法的有效性。

关键词: Web Service, 服务质量(QoS), 预测, 自回归求和移动平均(ARIMA), 时间序列

Abstract: The QoS (quality of service) of Web services will fluctuate according to the variations of Internet environment and server loads. Therefore, the key question in the service computing areas is how to help users select appropriate Web Service. This paper presents a Web Service QoS prediction method based on time series analysis to address the above question. And it accomplishes the tool of predicting Web Service QoS automatically. This tool can predict the QoS information in the short future according to the historic data of Web Service. And the experiments verify the effectiveness of the method based on the historic data from 17832 services.

Key words: Web Service, quality of service (QoS), prediction, autoregressive integrated moving average (ARIMA), time series