{"title":"高速分组接入网络的QoS预测","authors":"Yuting Sun, K. Tsang, H. Tung, K. L. Lam, K. Ko","doi":"10.1109/CCNC08.2007.182","DOIUrl":null,"url":null,"abstract":"By employing Bayesian neural network, a new QoS prediction algorithm for high speed packet access network has been developed. Network performances are evaluated based on a well developed call admission control scheme, namely the tri-threshold bandwidth reservation scheme. The algorithm helps to improve the resource management, thus saving the cost and bandwidth.","PeriodicalId":183858,"journal":{"name":"2008 5th IEEE Consumer Communications and Networking Conference","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"QoS Prediction for High Speed Packet Access Networks\",\"authors\":\"Yuting Sun, K. Tsang, H. Tung, K. L. Lam, K. Ko\",\"doi\":\"10.1109/CCNC08.2007.182\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"By employing Bayesian neural network, a new QoS prediction algorithm for high speed packet access network has been developed. Network performances are evaluated based on a well developed call admission control scheme, namely the tri-threshold bandwidth reservation scheme. The algorithm helps to improve the resource management, thus saving the cost and bandwidth.\",\"PeriodicalId\":183858,\"journal\":{\"name\":\"2008 5th IEEE Consumer Communications and Networking Conference\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 5th IEEE Consumer Communications and Networking Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CCNC08.2007.182\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 5th IEEE Consumer Communications and Networking Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCNC08.2007.182","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
QoS Prediction for High Speed Packet Access Networks
By employing Bayesian neural network, a new QoS prediction algorithm for high speed packet access network has been developed. Network performances are evaluated based on a well developed call admission control scheme, namely the tri-threshold bandwidth reservation scheme. The algorithm helps to improve the resource management, thus saving the cost and bandwidth.
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