Geolocation of Internet hosts enables a diverse and interesting new class of location-aware applications. Previous measurement-based approaches use reference hosts, called landmarks, with a well-known geographic location to provide the location estimation of a target host. This leads to a discrete space of answers, limiting the number of possible location estimates to the number of adopted landmarks. In contrast, we propose Constraint-Based Geolocation (CBG), which infers the geographic location of Internet hosts using multilateration with distance constraints, thus establishing a continuous space of answers instead of a discrete one. CBG accurately transforms delay measurements to geographic distance constraints, and then uses multilateration to infer the geolocation of the target host. Our experimental results show that CBG outperforms the previous measurement-based geolocation techniques. Moreover, in contrast to previous approaches, our method is able to assign a confidence region to each given location estimate. This allows a location-aware application to assess whether the location estimate is sufficiently accurate for its needs.

A number of recent papers in the networking community study the distance matrix defined by the node-to-node latencies in the Internet and, in particular, provide a number of quite successful distributed approaches that embed this distance into a low-dimensional Euclidean space. In such algorithms it is feasible to measure distances among only a linear or near-linear number of node pairs; the rest of the distances are simply not available. Moreover, for applications it is desirable to spread the load evenly among the participating nodes. Indeed, several recent studies use this ’fully distributed ’ approach and achieve, empirically, a low distortion for all but a small fraction of node pairs. This is concurrent with the large body of theoretical work on metric embeddings, but there is a fundamental distinction: in the theoretical approaches to metric embeddings, full and centralized access to the distance matrix is assumed and heavily used. In this paper we present the first fully distributed embedding algorithm with provable distortion guarantees for doubling metrics (which have been proposed as a reasonable abstraction of Internet latencies), thus providing some insight into the empirical success of the recent Vivaldi algorithm [7]. The main ingredient of our embedding algorithm is an improved fully distributed algorithm for a more basic problem of triangulation, where the triangle inequality is used to infer the distances that have not been measured; this problem received a considerable attention in the networking community, and has also been studied theoretically in [19]. We use our techniques to extend ɛ-relaxed embeddings and triangulations to infinite metrics and arbitrary measures, and to improve on the approximate distance labeling scheme of Talwar [36]. 1

We present Topology-based Geolocation (TBG), a novel approach to estimating the geographic location of arbitrary Internet hosts. We motivate our work by showing that 1) existing approaches, based on end-to-end delay measurements from a set of landmarks, fail to outperform much simpler techniques, and 2) the error of these approaches is strongly determined by the distance to the nearest landmark, even when triangulation is used to combine estimates from different landmarks. Our approach improves on these earlier techniques by leveraging network topology, along with measurements of network delay, to constrain host position. We convert topology and delay data into a set of constraints, then solve for router and host locations simultaneously. This approach improves the consistency of location estimates, reducing the error substantially for structured networks in our experiments on Abilene and Sprint. For networks with insufficient structural constraints, our techniques integrate external hints that are validated using measurements before being trusted. Together, these techniques lower the median estimation error for our university-based dataset to 67 km vs. 228 km for the best previous approach.

Abstract — In this paper we propose a new routing protocol

A highly accurate client-independent geolocation service stands to be an important goal for the Internet. Despite an extensive research effort and significant advances in this area, this goal has not yet been met. Motivated by the fact that the best results to date are achieved by utilizing additional ’hints ’ beyond inherently inaccurate delay-based measurements, we propose a novel geolocation method that fundamentally escalates the use of external information. In particular, many entities (e.g., businesses, universities, institutions) host their Web services locally and provide their actual geographical location on their Websites. We demonstrate that the information provided in this way, when combined with network measurements, represents a precious geolocation resource. Our methodology automatically extracts, verifies, utilizes, and opportunistically inflates such Web-based information to achieve high accuracy. Moreover, it overcomes many of the fundamental inaccuracies encountered in the use of absolute delay measurements. We demonstrate that our system can geolocate IP addresses 50 times more accurately than the best previous system, i.e., it achieves a median error distance of 690 meters on the corresponding data set. 1

Abstract — It is well accepted among the web community that local servers out-perform distant ones. This common knowledge dictates buying a local web-hosting plan for one's business. In this paper we show that, all other factors being equal, time zone influence on web traffic peak times might dictate migrating web-hosting plans. We performed simulation which shows that for entertainment, auctions and similar evening traffic sites- sites who's main clientele access is between 4:00PM and 2:00AM, distant servers actually outperform local ones and it's beneficial to migrate to remote hosts. The simulation suggests that moving web-hosted sites ±3 time zones away from local clientele decreases the total response times experienced by clients.