{"title":"Performance Prediction of Network-Intensive Systems in Cloud Environment: A Bayesian Approach","authors":"Ying Fan, Jianpeng Hu, Tianqi Sun","doi":"10.1109/EEI48997.2019.00085","DOIUrl":null,"url":null,"abstract":"The resource requirements of cloud applications varies with the load intensity, so it is necessary to predict resource changes in advance. In this paper, a Bayesian method is proposed to predict the bandwidth consumption and quality of service. First, log mining is used to extract feature variables, and a Bayesian model is constructed by using stepwise discriminant method to select characteristic variables that are crucial for prediction. Then Bayesian discriminant and Bayesian network are used to predict the bandwidth consumption and response time. At last, we use a real-running web system to evaluate the effectiveness and accuracy of this method. Comparing with other methods, it can get more accurate prediction result of the performance in the cloud environment.","PeriodicalId":150974,"journal":{"name":"2019 International Conference on Electronic Engineering and Informatics (EEI)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Electronic Engineering and Informatics (EEI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EEI48997.2019.00085","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
The resource requirements of cloud applications varies with the load intensity, so it is necessary to predict resource changes in advance. In this paper, a Bayesian method is proposed to predict the bandwidth consumption and quality of service. First, log mining is used to extract feature variables, and a Bayesian model is constructed by using stepwise discriminant method to select characteristic variables that are crucial for prediction. Then Bayesian discriminant and Bayesian network are used to predict the bandwidth consumption and response time. At last, we use a real-running web system to evaluate the effectiveness and accuracy of this method. Comparing with other methods, it can get more accurate prediction result of the performance in the cloud environment.