QoS prediction algorithm used in location-aware hybrid Web service

被引：0

作者：

Haihong, E. ^{[1
,2
]}

Junjie, Tong ^{[1
,2
]}

Meina, Song ^{[1
,2
]}

Junde, Song ^{[1
,2
]}

机构：

[1] School of Computer Science, Beijing University of Posts and Telecommunications, Beijing,100876, China

[2] Engineering Research Center of Information Networks, Ministry of Education, Beijing,100876, China

来源：

Journal of China Universities of Posts and Telecommunications | 2015年 / 22卷 / 01期

基金：

高等学校博士学科点专项科研基金;

关键词：

Web services - Location - Fault tolerance - Websites - Correlation methods - Quality of service;

D O I：

暂无

中图分类号：

O212 [数理统计];

学科分类号：

摘要：

Quality-of-Service (QoS) describes the non-functional characteristics of Web services. As such, the QoS is a critical parameter in service selection, composition and fault tolerance, and must be accurately determined by some type of QoS prediction method. However, with the dramatic increase in the number of Web services, the prediction failure caused by data sparseness has become a critical challenge. A new 'hybrid user-location-aware prediction based on weighted Adamic-Adar (WAA)' (HUWAA) was proposed. The implicit neighbor search was optimized by incorporating location factors. Meanwhile, the ability of the improved algorithms to solve the data sparsity problem was validated in experiments on public real world datasets. The new algorithm outperforms the existing of item-based pearson correlation coefficient (IPCC), user-based pearson correlation coefficient (UPCC) and Web service recommender system (WSRec) algorithms.

引用

页码：42 / 49