基于用户聚类和回归算法的QoS预测新方法

Yuliang Shi, Kun Zhang, Bing Liu, Li-zhen Cui
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引用次数: 19

摘要

QoS已成为web服务选择的重要指标。本文提出了一种可以为用户提供近似QoS值的方法,并支持找到最优的web服务。该方法首先根据用户的位置和网络状况对用户进行聚类,然后根据同一聚类中用户的QoS历史统计数据,采用线性回归算法预测基于调用时间和工作负载的QoS值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A New QoS Prediction Approach Based on User Clustering and Regression Algorithms
QoS has become an important measure for web service selection. In this paper, we present an approach which can provide the approximate QoS value for users, and support finding the optimal web service. Firstly, it clusters the users based on location and network condition, then according to the QoS historical statistics of users in the same cluster, uses the linear regression algorithm to predict the QoS value based on invocation time and workload.
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