基于结构化噪声矩阵补全的Web服务QoS预测

陈蕾; 杨庚; 陈正宇; 肖甫; 许建

doi:10.11959/j.issn.1000-436x.2015118

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基于结构化噪声矩阵补全的Web服务QoS预测

学术论文 | 更新时间：2024-06-05

- 基于结构化噪声矩阵补全的Web服务QoS预测
- Web services QoS prediction via matrix completion with structural noise
- 通信学报 2015年36卷第6期页码：49-59
- 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：
  
  [ "陈蕾（1975-），男，江西宜春人，博士，南京邮电大学副教授、硕士生导师，主要研究方向为可信服务计算、机器学习、数据挖掘。" ]
  [ "杨庚（1961-），男，江苏建湖人，博士，南京邮电大学教授、博士生导师，主要研究方向为计算机通信与网络、并行与分布式计算、信息安全。" ]
  [ "陈正宇（1978-），男，江苏淮安人，南京邮电大学博士生，主要研究方向为无线传感网数据融合、服务计算和隐私保护。" ]
  [ "肖甫（1980-），男，湖南邵阳人，博士，南京邮电大学教授、博士生导师，主要研究方向为无线传感器网络、云计算和多媒体图像检索等。" ]
  [ "许建（1980-），男，江苏徐州人，南京邮电大学副教授，主要研究方向为无线传感器网络与信息安全、智能信息处理。" ]
- 基金信息：
  
  国家自然科学基金资助项目(61272084);国家自然科学基金资助项目(61201163);国家自然科学基金资助项目(61272422);国家自然科学基金资助项目(61373137);江苏省自然科学基金资助项目(BK2011072);江苏省自然科学基金资助项目(BK20130096);江苏省高校自然科学研究重大基金资助项目(11KJA520002);高等学校博士学科点专项科研基金资助项目(20113223110003)
- DOI：10.11959/j.issn.1000-436x.2015118
  中图分类号： TP311
- 网络出版日期：2015-06，
  
  纸质出版日期：2015-06-25
- 稿件说明：
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陈蕾, 杨庚, 陈正宇, 等. 基于结构化噪声矩阵补全的Web服务QoS预测[J]. 通信学报, 2015,36(6):49-59.

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.
陈蕾, 杨庚, 陈正宇, 等. 基于结构化噪声矩阵补全的Web服务QoS预测[J]. 通信学报, 2015,36(6):49-59. DOI： 10.11959/j.issn.1000-436x.2015118.

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.

关键词

Keywords

references

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