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Title: Pushing the Boundaries with bdrmapIT: Mapping Router Ownership at Internet Scale
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.  more » « less
Award ID(s):
1724853
PAR ID:
10111809
Author(s) / Creator(s):
; ; ; ; ;
Date Published:
Journal Name:
Proceedings of the 2018 ACM SIGCOMM conference on Internet measurement conference - IMC '18
Page Range / eLocation ID:
56 to 69
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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