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Abstract:
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The localization of Internet hosts opens space for a
wide scope of applications, from targeted, location aware content
provision to localizing illegal content. In this paper we present a
novel probabilistic approach, called Spotter, for estimating the geographic
position of Internet devices with remarkable precision.
While the existing methods use landmark specific calibration for
building their internal models we show that the delay-distance
data follow a generic distribution for each landmark. Hence,
instead of describing the delay-distance space in a landmark
specific manner our proposed method handles all the calibration
points together and derives a common delay-distance model.
This fundamental discovery indicates that, in contrast to prior
techniques, Spotter is less prone to measurement errors and
other anomalies such as indirect routing. To demonstrate the
robustness and the accuracy of Spotter we test the performance
on PlanetLab nodes as well as on a more realistic reference
set collected by CAIDA explicitly for geolocation comparison
purposes. To the best of our knowledge, we are the first to use
this novel ground truth containing over 23000 network routers
with their geographic locations.
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