{"title":"流速度下IP网络流量的分形建模","authors":"Flip Korn, S. Muthukrishnan, Yihua Wu","doi":"10.1109/ICDE.2006.73","DOIUrl":null,"url":null,"abstract":"This paper describes how to fit fractal models, online, on IP traffic data streams. Our approach relies on maintaining a sketch of the data stream and fitting straight lines: it yields algorithms that are fast, space-efficient, and accurate. We implemented our methods in AT&T’s Gigascope data stream management system, to demonstrate their practicality at streaming line speeds.","PeriodicalId":6819,"journal":{"name":"22nd International Conference on Data Engineering (ICDE'06)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2006-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Fractal Modeling of IP Network Traffic at Streaming Speeds\",\"authors\":\"Flip Korn, S. Muthukrishnan, Yihua Wu\",\"doi\":\"10.1109/ICDE.2006.73\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper describes how to fit fractal models, online, on IP traffic data streams. Our approach relies on maintaining a sketch of the data stream and fitting straight lines: it yields algorithms that are fast, space-efficient, and accurate. We implemented our methods in AT&T’s Gigascope data stream management system, to demonstrate their practicality at streaming line speeds.\",\"PeriodicalId\":6819,\"journal\":{\"name\":\"22nd International Conference on Data Engineering (ICDE'06)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-04-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"22nd International Conference on Data Engineering (ICDE'06)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICDE.2006.73\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"22nd International Conference on Data Engineering (ICDE'06)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDE.2006.73","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Fractal Modeling of IP Network Traffic at Streaming Speeds
This paper describes how to fit fractal models, online, on IP traffic data streams. Our approach relies on maintaining a sketch of the data stream and fitting straight lines: it yields algorithms that are fast, space-efficient, and accurate. We implemented our methods in AT&T’s Gigascope data stream management system, to demonstrate their practicality at streaming line speeds.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
