An overview of the TACLO model, which aims to enhance the performance of VANETs through innovative routing and clustering strategies. With the rising concern over road safety and traffic congestion, VANETs emerge as a promising solution leveraging wireless technology. However, challenges such as routing efficiency, congestion, and quality of service persist. TACLO addresses these challenges by integrating reactive routing protocols like AODV with a traffic-aware clustering process, optimizing communication reliability and resource utilization. Additionally, the model employs Lion Optimization for optimal CH selection, enhancing data collection and transfer efficiency. Through comprehensive experimentation, the routing protocol within TACLO demonstrates significant improvements in packet delivery ratio, network throughput, energy efficiency, average delay, and routing overhead compared to existing techniques. These findings underscore the effectiveness of TACLO to revolutionize VANETs, improving road safety, traffic flow, and driving experience in dynamic vehicular environments.


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    Titel :

    Traffic-Aware Clustering and Optimal CH Selection Using Lion Optimization in Vehicular Ad Hoc Networks


    Beteiligte:
    Prasad, U. (Autor:in) / Chithra, L. (Autor:in) / Chowdary, CH. Mastan (Autor:in) / Mansour, I M A (Autor:in) / Bagde, S (Autor:in) / Ramesh, PGV. (Autor:in)


    Erscheinungsdatum :

    27.03.2025


    Format / Umfang :

    809523 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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