Yi-yong Lin, Yang Qiao, Shibin Hu, B. Dong, Xing-yuan Zhang
{"title":"Research on short-term flow prediction of local area network based on ARMA model","authors":"Yi-yong Lin, Yang Qiao, Shibin Hu, B. Dong, Xing-yuan Zhang","doi":"10.1117/12.2640665","DOIUrl":null,"url":null,"abstract":"The characteristics of the ARMA model are analyzed according to the characteristics of the short-term flow data of the local area network in this paper. The time prediction model of network flow is established on the ARMA method. The prediction parameters of the ARMA model are determined and the model is simulated According to the short-term flow prediction. The comparison between the simulation results and the measured data of NetFlow shows that the model can accurately predict the short-term flow behavior trend of the local area network, which can provide reference and reference for the analysis of network traffic behavior.","PeriodicalId":336892,"journal":{"name":"Neural Networks, Information and Communication Engineering","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Neural Networks, Information and Communication Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.2640665","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The characteristics of the ARMA model are analyzed according to the characteristics of the short-term flow data of the local area network in this paper. The time prediction model of network flow is established on the ARMA method. The prediction parameters of the ARMA model are determined and the model is simulated According to the short-term flow prediction. The comparison between the simulation results and the measured data of NetFlow shows that the model can accurately predict the short-term flow behavior trend of the local area network, which can provide reference and reference for the analysis of network traffic behavior.