Publication date: Available online 21 September 2016
Source:Decision Support Systems
Author(s): Shuai Ding, Zeyuan Wang, Desheng Wu, David L. Olson
With the rapid development of cloud computing, cloud service has become an indispensable component of modern information systems where quality of service (QoS) has a direct impact on the system performance and stability. While scholars have concentrated their efforts on the monitoring and evaluation of QoS in cloud computing, other service selection characteristics have been neglected, such as the scarcity of evaluation data and various customer needs. In this paper, we present a ranking-oriented prediction method that will assist in the process of discovering the cloud service candidates that have the highest customer satisfaction. This approach encompasses two basic functions: ranking similarity estimation and cloud service ranking prediction that takes into account customer's preference and expectation. The comparative experimental results show that the proposed method outperforms other competing methods.
Source:Decision Support Systems
Author(s): Shuai Ding, Zeyuan Wang, Desheng Wu, David L. Olson