The vehicular relay network remains a promising path of future intelligent transportation systems (ITS) that connects the autonomous vehicle with the internet for better traffic control and information sharing. The transmission control protocol (TCP) remains the backbone of data traffic on the internet as it harbors an enormous portion of global internet traffic between end devices. In VANET, TCP experiences drastic performance degradation during early or spurious RTO timeouts. This paper proposes a recursive learning retransmission timeout (RL-RTO), which efficiently reduces spurious timeouts and enhances fast recovery after timeouts. The RL-RTO forecast timer value is based on the three control parameters. The performance of RL-RTO is validated against recent RTO approaches under multi-hop vehicular environments. The proposed RL-RTO considerably regulates estimation errors and improves variance.


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    Titel :

    An Improved Retransmission Timeout Forecasting Algorithm for Vehicular Networks


    Beteiligte:
    Auxilius Jude, M Joseph (Autor:in) / Diniesh, V C (Autor:in) / K, Prathap Kumar (Autor:in) / S, Rahul (Autor:in) / S, Nithish Kumar (Autor:in) / E N, Shanjeev (Autor:in)


    Erscheinungsdatum :

    21.04.2022


    Format / Umfang :

    1662578 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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