@unpublished{,
    author = {Hillmann, Peter; Schopp, Matthias; Stiemert, Lars},
    title = {On the Path to High Precise IP Geolocation : A Self-Optimizing Model},
    editor = {},
    booktitle = {},
    series = {},
    journal = {},
    address = {},
    publisher = {},
    edition = {},
    year = {2017},
    isbn = {},
    volume = {},
    number =  {},
    pages = {},
    url = {},
    doi = {},
    keywords = {IP Geolocation ; Lateration ; Network Security},
    abstract = {IP Geolocation is a key enabler for the Future
Internet to provide geographical location
information for application services. For example,
this data is used by Content Delivery Networks to
assign users to mirror servers, which are close by,
hence providing enhanced traffic management. It is
still a challenging task to obtain precise and stable
location information, whereas proper results are only
achieved by the use of active latency measurements.
This paper presents an advanced approach for an
accurate and self-optimizing model for location
determination, including identification of optimized
Landmark positions, which are used for probing.
Moreover, the selection of correlated data and the
estimated target location requires a sophisticated
strategy to identify the correct position. We present
an improved approximation of network distances of
usually unknown TIER infrastructures using the road
network. Our concept is evaluated under real-world
conditions focusing Europe.},
    note = {Vortrag bei Workshop bei RUAG, Bern},
    institution = {Universität der Bundeswehr München, Fakultät für Informatik, INF 3 - Institut für Technische Informatik, Professur: },
    
    
}