Web services QoS prediction via matrix completion with structural noise

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Web services QoS prediction via matrix completion with structural noise

Academic paper | 更新时间：2024-06-05

- Web services QoS prediction via matrix completion with structural noise
- Journal on Communications Vol. 36, Issue 6, Pages: 49-59(2015)
- 作者机构：
  
  1. 南京邮电大学计算机学院，江苏南京 210003
  2. 南京邮电大学宽带无线通信与传感网技术教育部重点实验室，江苏南京 210003
- 作者简介：
- 基金信息：
  
  The National Natural Science Program of China(61272084);The National Natural Science Foundation of China(61201163);The National Natural Science Foundation of China(61272422);The National Natural Science Foundation of China(61373137);The Natural Science Foundation of Jiangsu Province(BK2011072);The Natural Science Foundation of Jiangsu Province(BK20130096);The Natural Science Foundation for Colleges and Universities of Jiangsu Province(11KJA520002);The Research Fund for the Doctoral Program of Higher Education of China(20113223110003)
- DOI：10.11959/j.issn.1000-436x.2015118
  CLC： TP311
- Online First：2015-06，
  
  Published：25 June 2015
- 稿件说明：
移动端阅览
Lei CHEN, Geng YANG, Zheng-yu CHEN, et al. Web services QoS prediction via matrix completion with structural noise[J]. Journal on Communications, 2015, 36(6): 49-59.
DOI：

Lei CHEN, Geng YANG, Zheng-yu CHEN, et al. Web services QoS prediction via matrix completion with structural noise[J]. Journal on Communications, 2015, 36(6): 49-59. DOI： 10.11959/j.issn.1000-436x.2015118.

摘要

随着面向服务计算技术的快速发展，越来越多具有相同或相似功能的 Web 服务被部署在网络上。用户进行服务选择之前，通常需要根据历史调用信息对未使用过的服务QoS进行预测。由于历史调用信息收集过程缺乏有效的监督和约束机制，所采样的QoS信息往往容易受到结构化噪声污染，从而导致现有方法预测性能急剧下降。为了克服这个困难，通过将Web服务QoS预测问题建模为L2

1范数正则化矩阵补全问题，提出了一类基于结构化噪声矩阵补全的Web服务QoS预测方法。真实数据集上的实验结果表明，该方法不仅能精确地辨识出QoS采样矩阵中噪声行所在位置，而且能对缺失Web服务QoS进行有效预测。

Abstract

With the rapid development of service-oriented computing

more and more Web services with the same or similar function are deployed on the Internet. Usually

before selecting the most suitable service

users need to predict QoS of unused services from the service invoking history. Due to the lack of effective supervision and constraint mechanisms

some number of the rows in the QoS sample matrix is often contaminated by the structural noise

which leads to a sharp decrease for QoS prediction performance. In order to address this problem

an efficient Web services QoS prediction approach via matrix completion with structural noise is proposed by formulating Web services QoS prediction problem as a L2

1-norm regularized matrix completion problem. The proposed approach can not only exactly detect the position where the data is contaminated

but also effectively predict the missing QoS values. Finally

experimental results performed on a real public dataset demonstrate the feasibility of our proposed approach.

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Keywords

references

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