Upcoming connected vehicle applications will rely on large amounts of data to provide safety or comfort functionalities. Delivering such data, reliably on time is a challenge due to the inherent mobility in connected vehicle environments. The Information-Centric Networking (ICN) paradigm is a promising candidate to tackle the challenges of such environments. Addressing data by name instead of location, and the resulting capabilities such as in-network caching, make it a good fit for scenarios with a high degree of mobility. In this paper, we propose and evaluate an adaptive decentralized prefetching mechanism for ICNs in vehicular scenarios. By proactively placing relevant data in caches near to consumers, the overall service quality and delivery rate in the network is improved. The algorithm is evaluated using simulations based on a real V2X highway testbed in Austria.


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    Title :

    ADePt: Adaptive Distributed Content Prefetching for Information-Centric Connected Vehicles


    Contributors:


    Publication date :

    2018-06-01


    Size :

    692827 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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