Alexander Marder, M. Luckie, A. Dhamdhere, B. Huffaker, K. Claffy, Jonathan M. Smith
{"title":"Pushing the Boundaries with bdrmapIT: Mapping Router Ownership at Internet Scale","authors":"Alexander Marder, M. Luckie, A. Dhamdhere, B. Huffaker, K. Claffy, Jonathan M. Smith","doi":"10.1145/3278532.3278538","DOIUrl":null,"url":null,"abstract":"Two complementary approaches to mapping network boundaries from traceroute paths recently emerged [27,31]. Both approaches apply heuristics to inform inferences extracted from traceroute measurement campaigns. bdrmap [27] used targeted traceroutes from a specific network, alias resolution probing techniques, and AS relationship inferences, to infer the boundaries of that specific network and the other networks attached at each boundary. MAPIT [31] tackled the ambitious challenge of inferring all AS-level network boundaries in a massive archived collection of traceroutes launched from many different networks. Both were substantial contributions to the state-of-the-art, and inspired a collaboration to explore the potential to combine the approaches. We present and evaluate bdrmapIT, the result of that exploration, which yielded a more complete, accurate, and general solution to this persistent and central challenge of Internet topology research. bdrmapIT achieves 91.8%-98.8% accuracy when mapping AS boundaries in two Internet-wide traceroute datasets, vastly improving on MAP-IT's coverage without sacrificing bdrmap's ability to map a single network. The bdrmapIT source code is available at https://git.io/fAsI0.","PeriodicalId":20640,"journal":{"name":"Proceedings of the Internet Measurement Conference 2018","volume":"41 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2018-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"58","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Internet Measurement Conference 2018","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3278532.3278538","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 58
Abstract
Two complementary approaches to mapping network boundaries from traceroute paths recently emerged [27,31]. Both approaches apply heuristics to inform inferences extracted from traceroute measurement campaigns. bdrmap [27] used targeted traceroutes from a specific network, alias resolution probing techniques, and AS relationship inferences, to infer the boundaries of that specific network and the other networks attached at each boundary. MAPIT [31] tackled the ambitious challenge of inferring all AS-level network boundaries in a massive archived collection of traceroutes launched from many different networks. Both were substantial contributions to the state-of-the-art, and inspired a collaboration to explore the potential to combine the approaches. We present and evaluate bdrmapIT, the result of that exploration, which yielded a more complete, accurate, and general solution to this persistent and central challenge of Internet topology research. bdrmapIT achieves 91.8%-98.8% accuracy when mapping AS boundaries in two Internet-wide traceroute datasets, vastly improving on MAP-IT's coverage without sacrificing bdrmap's ability to map a single network. The bdrmapIT source code is available at https://git.io/fAsI0.