Run Huang, Mengying Zhou, Tiancheng Guo, Yang Chen
{"title":"定位带有HTTP响应的CDN边缘服务器","authors":"Run Huang, Mengying Zhou, Tiancheng Guo, Yang Chen","doi":"10.1145/3546037.3546051","DOIUrl":null,"url":null,"abstract":"Determining the physical locations of CDN Points of Presence (PoPs) is fundamental to understanding and diagnosing CDN services. Yet, the popular deployment of IP Anycast in CDNs has rendered existing geolocation tools unreliable. To fill this gap, we present an HTTP-based solution that leverages subtle geographic hints in HTTP responses to locate CDN PoPs at the city-level granularity. The evaluation shows that our technique achieves over 90% accuracy with an average error distance of less than 40 km.","PeriodicalId":351682,"journal":{"name":"Proceedings of the SIGCOMM '22 Poster and Demo Sessions","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Locating CDN edge servers with HTTP responses\",\"authors\":\"Run Huang, Mengying Zhou, Tiancheng Guo, Yang Chen\",\"doi\":\"10.1145/3546037.3546051\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Determining the physical locations of CDN Points of Presence (PoPs) is fundamental to understanding and diagnosing CDN services. Yet, the popular deployment of IP Anycast in CDNs has rendered existing geolocation tools unreliable. To fill this gap, we present an HTTP-based solution that leverages subtle geographic hints in HTTP responses to locate CDN PoPs at the city-level granularity. The evaluation shows that our technique achieves over 90% accuracy with an average error distance of less than 40 km.\",\"PeriodicalId\":351682,\"journal\":{\"name\":\"Proceedings of the SIGCOMM '22 Poster and Demo Sessions\",\"volume\":\"9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-08-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the SIGCOMM '22 Poster and Demo Sessions\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3546037.3546051\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the SIGCOMM '22 Poster and Demo Sessions","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3546037.3546051","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Determining the physical locations of CDN Points of Presence (PoPs) is fundamental to understanding and diagnosing CDN services. Yet, the popular deployment of IP Anycast in CDNs has rendered existing geolocation tools unreliable. To fill this gap, we present an HTTP-based solution that leverages subtle geographic hints in HTTP responses to locate CDN PoPs at the city-level granularity. The evaluation shows that our technique achieves over 90% accuracy with an average error distance of less than 40 km.