Similarity models for Internet host location

A whole new class of location-aware services may be envisaged by the deployment of a geographic location service for Internet hosts. We focus on a technique that relies on delay measurements and the exploitation of a possible correlation between geographic distance and network delay. Our investigation shows that such a correlation becomes stronger as connectivity becomes richer. Host locations are inferred by comparing delay patterns of geographically distributed landmarks (hosts with a known geographic location) with the delay pattern of the target host to be located. The problem we deal with is how to best measure the similarity between the delay patterns of the landmarks and the one observed for the target host. The location estimation of the target host is the location of the landmark that presents the most similar delay pattern with respect to the one of the target host. We define and evaluate three similarity models. Experiments show that the previously adopted Euclidean distance is outperformed by other similarity models, resulting in a more accurate Internet host location from delay measurements.