QoS Ranking Prediction for Cloud Services
QoS Ranking Prediction for Cloud Services
复制标题
云服务的QoS排名预测
DOI：
10.1109/tpds.2012.285
复制
发表时间：
2013-06-01
影响因子：
5.3
通讯作者：
Wang, Jianmin
中科院分区：
文献类型：
--
作者：
Zheng, Zibin;Wu, Xinmiao;Wang, Jianmin
云计算正变得越来越流行。构建高质量的云应用程序是一个关键的研究问题。QoS排名为从一组功能等效的候选服务中进行最佳云服务选择提供了有价值的信息。为了获得QoS值，通常需要对候选服务进行实际调用。为了避免实际服务调用的耗时和昂贵，本文通过利用其他消费者过去的服务使用经验，提出了一个云服务的QoS排名预测框架。我们提出的框架在进行QoS排名预测时不需要额外调用云服务。提出了两种个性化的QoS排名预测方法来直接预测QoS排名。利用真实世界的QoS数据，包括300个分布在世界各地的用户和500个真实世界的web服务进行了全面的实验。实验结果表明，我们的方法优于其他竞争方法。
Cloud computing is becoming popular. Building high-quality cloud applications is a critical research problem. QoS rankings provide valuable information for making optimal cloud service selection from a set of functionally equivalent service candidates. To obtain QoS values, real-world invocations on the service candidates are usually required. To avoid the time-consuming and expensive real-world service invocations, this paper proposes a QoS ranking prediction framework for cloud services by taking advantage of the past service usage experiences of other consumers. Our proposed framework requires no additional invocations of cloud services when making QoS ranking prediction. Two personalized QoS ranking prediction approaches are proposed to predict the QoS rankings directly. Comprehensive experiments are conducted employing real-world QoS data, including 300 distributed users and 500 real-world web services all over the world. The experimental results show that our approaches outperform other competing approaches.