Statistical Geolocation of Internet Hosts

Abstract—Automated,geolocation,of IP addresses,has impor- tant applications to targeted delivery of local news, advertising and other content over the Internet. Previous measurement-based approaches,to geolocation,employ,active probing,to measure delays among,a set of landmark,nodes,with,known,locations. The location of a target IP address,can,be approximated,by that of the nearest landmark, as determined by the delay measurements. To improve geolocation accuracy, a variation of this approach,uses multilateration,with geographic,distance constraints to obtain a continuous,location space rather than the discrete set of landmark,locations. Since the previous approaches are fundamentally deterministic, they can only provide relatively loose bounds,on the true location of an IP address. We develop a statistical geolocation,scheme,based on applying,kernel density estimation to delay measurements,among,a set of landmarks. An estimate,of the target location is then obtained,by maximizing the likelihood of the distances from the target to the landmarks, given the measured,delays. This is achieved,by an algorithm which,combines,gradient ascent and,force-directed methods. We present,experimental,results on PlanetLab to demonstrate,the