Team for Research in
Ubiquitous Secure Technology

Geolocalization on the Internet through Constraint Satisfaction
Bernard Wong, Ivan Stoyanov, Emin Gun Sirer

Citation
Bernard Wong, Ivan Stoyanov, Emin Gun Sirer. "Geolocalization on the Internet through Constraint Satisfaction". Proceedings of Workshop on Real, Large Distributed Systems (WORLDS), Workshop on Real, Large Distributed Systems (WORLDS), November, 2006.

Abstract
This paper outlines a novel, comprehensive framework for geolocalization, that is, determining the physical location of Internet hosts based on network measurements. The core insight behind this framework is to pose the geolocalization problem formally as one of error-minimizing constraint satisfaction, to create a system of constraints by deriving them aggressively from network measurements, and to solve the system using cheap and accurate geometric methods. The framework is general and accommodates both positive and negative constraints, that is, constraints on where the node can or cannot be, respectively. It can reason in the presence of uncertainty, enabling it to gracefully cope with aggressively derived constraints that may contain errors. Since the solution space is represented geometrically as a region bounded by Bezier curves, the framework yields an accurate set of all points where the target may be located. Preliminary results on PlanetLab show promise; the framework can localize the median node to within 22 miles, a factor of three better than previous approaches, with little error.

Electronic downloads

Citation formats  
  • HTML
    Bernard Wong, Ivan Stoyanov, Emin Gun Sirer. <a
    href="http://www.truststc.org/pubs/179.html"
    >Geolocalization on the Internet through Constraint
    Satisfaction</a>, Proceedings of Workshop on Real,
    Large Distributed Systems (WORLDS), Workshop on Real, Large
    Distributed Systems (WORLDS), November, 2006.
  • Plain text
    Bernard Wong, Ivan Stoyanov, Emin Gun Sirer.
    "Geolocalization on the Internet through Constraint
    Satisfaction". Proceedings of Workshop on Real, Large
    Distributed Systems (WORLDS), Workshop on Real, Large
    Distributed Systems (WORLDS), November, 2006.
  • BibTeX
    @inproceedings{WongStoyanovSirer06_GeolocalizationOnInternetThroughConstraintSatisfaction,
        author = {Bernard Wong and Ivan Stoyanov and Emin Gun Sirer},
        title = {Geolocalization on the Internet through Constraint
                  Satisfaction},
        booktitle = {Proceedings of Workshop on Real, Large Distributed
                  Systems (WORLDS)},
        organization = {Workshop on Real, Large Distributed Systems
                  (WORLDS)},
        month = {November},
        year = {2006},
        abstract = {This paper outlines a novel, comprehensive
                  framework for geolocalization, that is,
                  determining the physical location of Internet
                  hosts based on network measurements. The core
                  insight behind this framework is to pose the
                  geolocalization problem formally as one of
                  error-minimizing constraint satisfaction, to
                  create a system of constraints by deriving them
                  aggressively from network measurements, and to
                  solve the system using cheap and accurate
                  geometric methods. The framework is general and
                  accommodates both positive and negative
                  constraints, that is, constraints on where the
                  node can or cannot be, respectively. It can reason
                  in the presence of uncertainty, enabling it to
                  gracefully cope with aggressively derived
                  constraints that may contain errors. Since the
                  solution space is represented geometrically as a
                  region bounded by Bezier curves, the framework
                  yields an accurate set of all points where the
                  target may be located. Preliminary results on
                  PlanetLab show promise; the framework can localize
                  the median node to within 22 miles, a factor of
                  three better than previous approaches, with little
                  error.},
        URL = {http://www.truststc.org/pubs/179.html}
    }
    

Posted by Kelly Patwell on 13 Feb 2007.
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