IP geolocation in metropolitan areas

Authors:
Satinder Pal Singh;Randolph Baden;Choon Lee;Bobby Bhattacharjee;Richard La;Mark Shayman
Affiliations:
Unviersity of Maryland College Park, College Park, MD, USA;Unviersity of Maryland College Park, College Park, MD, USA;Unviersity of Maryland College Park, College Park, MD, USA;Unviersity of Maryland College Park, College Park, MD, USA;Unviersity of Maryland College Park, College Park, MD, USA;Unviersity of Maryland College Park, College Park, MD, USA
Venue:
Proceedings of the ACM SIGMETRICS joint international conference on Measurement and modeling of computer systems
Year:
2011

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Abstract

Current IP geoloation techniques can geolocate an IP address to a region approximately 700 square miles, roughly the size of a metropolitan area. We model geolocation as a pattern-recognition problem, and introduce techniques that geolocate addresses to within 5 miles inside a metropolitan area. We propose two complementary algorithms: The first algorithm, Pattern Based Geolocation (PBG), models the distribution of latencies to the target and compares it to those of the reference landmarks to resolve an address to within 5 miles in a metropolitan area. The second approach, Perturbation Augmented PBG (PAPBG), provides higher resolution by sending extra traffic in the network. While sending an aggregate of 600 Kbps extra traffic to 20 nodes for approximately 2 minutes, PAPBG geolocates addresses to within 3 miles.