HLOC: Hints-Based Geolocation Leveraging Multiple Measurement Frameworks

Geographically locating an IP address is of interest for many purposes. There are two major ways to obtain the location of an IP address: querying commercial databases or conducting latency measurements. For structural Internet nodes, such as routers, commercial databases are limited by low accuracy, while current measurement-based approaches overwhelm users with setup overhead and scalability issues. In this work we present our system HLOC, aiming to combine the ease of database use with the accuracy of latency measurements. We evaluate HLOC on a comprehensive router data set of 1.4M IPv4 and 183k IPv6 routers. HLOC first extracts location hints from rDNS names, and then conducts multi-tier latency measurements. Configuration complexity is minimized by using publicly available large-scale measurement frameworks such as RIPE Atlas. Using this measurement, we can confirm or disprove the location hints found in domain names. We publicly release HLOC's ready-to-use source code, enabling researchers to easily increase geolocation accuracy with minimum overhead.Comment: As published in TMA'17 conference: http://tma.ifip.org/main-conference

Towards geolocation of millions of IP addresses

Previous measurement-based IP geolocation algorithms have focused on accuracy, studying a few targets with increasingly sophisticated algorithms taking measurements from tens of vantage points (VPs). In this paper, we study how to scale up existing measurement-based geolocation algorithms like Shortest Ping and CBG to cover the whole Internet. We show that with many vantage points, VP proximity to the target is the most important factor affecting accuracy. This observation suggests our new algorithm that selects the best few VPs for each target from many candidates. This approach addresses the main bottleneck to geolocation scalability: minimizing traffic into each target (and also out of each VP) while maintaining accuracy. Using this approach we have currently geolocated about 24 % of the allocated, unicast, IPv4 address-space (about 55 % of the addresses in the Internet that can be directly geolocated). 1