Vehicle ad hoc networks (VANETs) research is crucial to intelligent transportation systems (ITS). VANETs provide infrastructure-motor vehicle communication for intelligent traffic management and accident prevention at low cost. Traffic is increasing, particularly in crowded areas, making traffic monitoring harder. Since transportation technology is becoming fundamental to modern life, safety risks from increased car usage must be addressed. A multinational consortium of manufacturers found that the creation of more than 97 million automobiles a year contributes to traffic-related fatalities, which kill millions globally. VANETs may reduce accidents by collecting and sharing safety data. This paper examines cluster-based VANET authentication systems, their advantages, limitations, and applications. It explores how secure key management systems might improve authentication. This study analyzes many systems utilizing throughput, detection rate, security, packet delivery ratio, and end-to-end latency after analyzing the literature and identifying research needs. This paper introduces a VANET clustering mechanism that improves network stability. The proposed approach beats state-of-the-art clustering methods in recall, accuracy, precision, computation time, and F1-score. The study provides a certification authority-secured vehicle authentication key management system to increase VANET event signal distribution trustworthiness.


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    Titel :

    Enhanced Optimization Algorithm for Energy-Efficient Clustering to Ensure Stability in VANETs


    Weitere Titelangaben:

    Smart Innovation, Systems and Technologies


    Beteiligte:
    Poonia, Ramesh Chandra (Herausgeber:in) / Sharma, Sugam (Herausgeber:in) / Hameed, Ibrahim A. (Herausgeber:in) / Upreti, Kamal (Herausgeber:in) / Vijayakumari, L. (Autor:in) / Gurumoorthy, K. B. (Autor:in)

    Kongress:

    International Conference on Smart Cyber Physical Systems ; 2024 ; Delhi, India September 13, 2024 - September 14, 2024



    Erscheinungsdatum :

    15.07.2025


    Format / Umfang :

    15 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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