Dipl.-Inf.

Roscher, Karsten

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  • Publication
    Know thy neighbor - a data-driven approach to neighborhood estimation in VANETs
    ( 2017)
    Roscher, Karsten
    ;
    Nitsche, Thomas
    ;
    Knorr, Rudi
    Current advances in vehicular ad-hoc networks (VANETs) point out the importance of multi-hop message dissemination. For this type of communication, the selection of neighboring nodes with stable links is vital. In this work, we address the neighbor selection problem with a data-driven approach. To this aim, we apply machine learning techniques to a massive data-set of ETSI ITS message exchange samples, obtained from simulated traffic in the highly detailed Luxembourg SUMO Traffic (LuST) Scenario. As a result, we present classification methods that increase neighbor selection accuracy by up to 43% compared to the state of the art.