计算机应用与软件2017，Vol.34Issue(11)：34-38,69,6.DOI:10.3969/j.issn.1000-386x.2017.11.006
基于改进贝叶斯算法的云服务可靠性预测方法研究
CLOUD SERVICE RELIABILITY PREDICTION METHOD BASED ON IMPROVED BAYES
摘要
Abstract
In view of the continuous development of the service consumer business and the complexity of the business logic,the demand for reliability of the cloud service composition is increasing.Through the prediction of the reliability of service composition,according to the prediction results,the service composition was recommended to service consumers to satisfy their reliability requirements to improve the service quality.We propose an improved Bayesian prediction algorithm based on the traditional Bayesian prediction model.By using the exponential weighted regression method to estimate the variance term of the state error in the algorithm,the problem of difficulty in determining the variance parameters of state error in the traditional Bayesian model is solved effectively.And it has high predictive efficiency and predictive accuracy.The experimental results show that the improved Bayesian prediction algorithm has higher accuracy than other traditional time series prediction algorithms.关键词
服务组合/可靠性/贝叶斯模型/预测Key words
Service composition/Reliability/Bayesian model/Prediction分类
信息技术与安全科学引用本文复制引用
钱双洋,陈喆,刘原序..基于改进贝叶斯算法的云服务可靠性预测方法研究[J].计算机应用与软件,2017,34(11):34-38,69,6.基金项目
国家高技术发展研究计划项目(2008AA01Z404) （2008AA01Z404）
国防预研基金项目(9140A26010306JB5201). （9140A26010306JB5201）
