Recently, finding the geographic whereabouts of nodes became a key service for many distributed applications, e.g., online games or localizing delivered content. However, an exact localization may be impossible because of GPS signals being unavailable, receivers too expensive, or energy too scarce. Hence,alternatives emerged that typically rely on central databases, which in turn are often found to be inaccurate, though. Facing that problem, we study a complementary idea: By constructing a delay-weighted spring-mass embedding of nodes and augmenting the system with geographic hints, e.g., those of traditional location databases, we efficiently estimate geographic positions of nodes by multilateration and solely distributed means. We will show that peer positions can be estimated with an accuracy of a few hundred kilometers in the average case. The proposed system is evaluated by simulations that are based on real-world PlanetLab latency data.

To support position-dependent services, like matchmaking algorithms for online games or geographic backup routes, the estimation of peer locations became a key requisite for a range of applications, recently. However, exact localization may be impossible, e.g., due to nodes lacking Global Positioning System (GPS) access for reasons of cost, energy, or signal unavailability. Alternative approaches, e.g., by nearby WLAN BSSIDs or IP geolocation, rely on databases and normally contain large outliers, in particular when concerning underrepresented mapping locations. This led us to the study of a complementary idea: By embedding nodes on a sphere and periodically minimizing local positioning errors by delay-based multilateration, we efficiently estimate node positions by distributed means, given a fair amount of position hints. Based on simulations that rely on real-world PlanetLab latency data, we show that global-scope peer locations can be estimated with an accuracy of a few hundred kilometers, where the novel approach outperforms a previously proposed spring-mass-based method by about 50%.

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Virtual private networks (VPNs) play an integral role in corporate and governmental communication systems nowadays. As such they are by definition an exposed target for attacks on the availability of whole communication infrastructures. A comparably effective way to disturb VPNs is the announcement of the involved IP address ranges by compromised BGP routers. Since in the foreseeable future criminals may focus on such attacks, this article discusses the intelligent creation of backup paths in the context of VPNs as a countermeasure. The proposed system is evaluated in simulations as well as in a prototypic environment.