In recent years, the prominence of vehicular ad hoc networks (VANETs) have significantly grown, emerging as a pivotal technology for enhancing road safety, traffic efficiency, and the overall driving experience. However, the dynamic and resource-constrained nature of VANETs presents a substantial challenge to efficient communication and network sustainability. In response to these challenges, energy-efficient optimal routing schemes have garnered considerable attention as a potential solution. This review paper provides a comprehensive analysis of various energy-efficient optimal routing schemes tailored for VANET systems. The study meticulously examines the principles and methodologies of geographic-based routing, prediction-based routing, and load-balanced routing algorithms. The focus is on how these algorithms can effectively reduce energy consumption while ensuring reliable data transmission. Additionally, the review underscores the importance of energy-aware routing decisions, offering insights into the strengths and limitations of existing routing approaches. It is my belief that the findings of this study offer valuable insights into the design of energy-efficient routing schemes capable of extending the lifespan of VANETs and meeting the dynamic demands of vehicular environments. Furthermore, it is essential to note that a substantial part of this field pertains to nerve-related conditions within the musculoskeletal system, encompassing issues such as nerve compression and nerve injuries.


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    Title :

    Investigating Energy-Efficient Optimal Routing Protocols for VANETs: A Comprehensive Study


    Additional title:

    Lect. Notes in Networks, Syst.


    Contributors:

    Conference:

    International Conference on Information and Communication Technology for Intelligent Systems ; 2024 ; Ahmedabad, India April 04, 2024 - April 05, 2024



    Publication date :

    2024-10-29


    Size :

    11 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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