{"title":"一种改进的自相似流量快速模拟算法及其在ATM网络中的应用","authors":"D. G. Daut, Ming Yu","doi":"10.1109/PACRIM.1999.799466","DOIUrl":null,"url":null,"abstract":"This paper presents an improved self-similar traffic generator, based on fast fractional Gaussian noise, for the purpose of fast simulation of long term correlation of self-similar traffic. The algorithm developed in this study is more efficient than existing methods since it only requires Hurst parameter and can arrive higher accurate sample points if necessary. The effectiveness of these methods has been demonstrated by some numerical examples.","PeriodicalId":176763,"journal":{"name":"1999 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM 1999). Conference Proceedings (Cat. No.99CH36368)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1999-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"An improved fast algorithm for simulating self-similar traffic with application in ATM networks\",\"authors\":\"D. G. Daut, Ming Yu\",\"doi\":\"10.1109/PACRIM.1999.799466\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents an improved self-similar traffic generator, based on fast fractional Gaussian noise, for the purpose of fast simulation of long term correlation of self-similar traffic. The algorithm developed in this study is more efficient than existing methods since it only requires Hurst parameter and can arrive higher accurate sample points if necessary. The effectiveness of these methods has been demonstrated by some numerical examples.\",\"PeriodicalId\":176763,\"journal\":{\"name\":\"1999 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM 1999). Conference Proceedings (Cat. No.99CH36368)\",\"volume\":\"70 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1999-08-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"1999 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM 1999). Conference Proceedings (Cat. No.99CH36368)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PACRIM.1999.799466\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"1999 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM 1999). Conference Proceedings (Cat. No.99CH36368)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PACRIM.1999.799466","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An improved fast algorithm for simulating self-similar traffic with application in ATM networks
This paper presents an improved self-similar traffic generator, based on fast fractional Gaussian noise, for the purpose of fast simulation of long term correlation of self-similar traffic. The algorithm developed in this study is more efficient than existing methods since it only requires Hurst parameter and can arrive higher accurate sample points if necessary. The effectiveness of these methods has been demonstrated by some numerical examples.
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