This work investigates through simulation the effectiveness of Slotted ALOHA for vehicular Medium Access Control (MAC), which is affected by dynamic changes in traffic and vehicular movements. The objective is to reach acceptable level of throughput with fewer collisions under changing environment. The presented work proposes a new dynamic method to enable constant modification of the vehicles (nodes) slots status and readiness to transmit, by responding to the continuous change in vehicular density. This enables adaptive control of transmitting slots and allow to sustain data load (traffic) and throughput within an acceptable limits, regardless of traffic density. This is achieved by minimize collisions in response to traffic and throughput adaptive behavior. The objective of collision reduction and throughput improvement is achieved using a dynamic load line, which operates using a central dynamic point (Q-point), where a slope is built around this point. The location and value of such point is determined by mathematical expression used to constantly update the Packet Ready Probability (PCKprob), number of vehicles (Vi), with subsequent change in Collision Probability (Cp) and both traffic (G) and throughput values (S). The derived mathematical model, show promising results in terms of optimizing the conventional Slotted ALOHA and improving the vehicular connectivity. The work analyzed the performance of Slotted ALOHA with the realization that it suffers from main disadvantage at high vehicular density as throughput drops with increase in collision probability. The new proposed method would help in improving the performance of Slotted ALOHA.


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    Titel :

    Vehicular Connectivity Analysis Using Enhanced Quality Slotted ALOHA (EQS-ALOHA)


    Weitere Titelangaben:

    Lect. Notes in Networks, Syst.


    Beteiligte:
    Arai, Kohei (Herausgeber:in) / Iskandarani, Mahmoud Zaki (Autor:in)

    Kongress:

    Science and Information Conference ; 2024 ; London, United Kingdom June 26, 2024 - June 27, 2024


    Erschienen in:

    Intelligent Computing ; Kapitel : 31 ; 484-509


    Erscheinungsdatum :

    15.06.2024


    Format / Umfang :

    26 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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