Uncertain QoS-Aware Skyline Service Selection Based on Cloud Model

Abstract

由于传统QoS感知的Web 服务选择方法无法保证服务选择的可靠性和实时性,提出了一种基于云模型的不确定性QoS 感知的Skyline 服务选择方法.该方法首先通过云模型计算QoS 的不确定性,然后采用Skyline 计算提取Web 服务中的Skyline 服务,剔除冗余服务,最后采用混合整数规划在Skyline 服务中进行服务选择.在公共有效数据集和合成数据集上的实验结果表明,所提出的方法能够为用户提供可靠、快速的服务选择.;Because traditional QoS-aware Web service selection approach cannot ensure the reliability and the real-time of service selection, this paper proposes an uncertain QoS-aware Skyline service selection approach based on cloud model. The approach first uses cloud model to compute the uncertainty of QoS and then adopts Skyline computing to extract Skyline services from Web services to prune redundant services. Finally, mixed integer programming is employed to perform service selection from Skyline services. The study evaluates the approach experimentally using both real and synthetically generated datasets. The experimental results show that the proposed approach can accomplish service selection for users reliably and quickly.