Researchers have become interested in vehicular ad hoc networks (VANETs) because they are crucial for developing intelligent transportation systems (ITS). The network packets are being send by all of the vehicles. As a result, the network bandwidth is heavily utilized, which causes the problem known as a network traffic. Duplicated rebroadcasting messages during message transmission via VANET networks increased message delivery time, increased channel busy ratio, increased collisions, wasted bandwidth, decreased packet delivery ratio, increased packet volume, etc. A suggests a two new method that should be taken into account for lowering the quantity of messages that are retransmitted or re-broadcast throughout the VANET network in the first technique while used elephant swarm water search algorithm (ESWSA) is proposed for node clustering in VANETs to achieve optimal cluster network vehicular nodes (CH) selection. This ESWSA technique minimizes network overhead in unexpected node density. Simulation results of ESWSA showed superior transmission range, node density, network area, and number of clusters than competitive other swarm clustering protocols. In order to manage re-broadcast traffic while reducing the quantity of duplicated traffic throughout the network, a new technique and algorithm for the effective dissemination of broadcast traffic of applications in VANET communication systems are proposed in this study. The vehicle will rebroadcast the packet if the timer expires and no duplicate message is received. The suggested algorithm instructs the vehicles to look for other nearby vehicles that are transmitting. With this procedure, the vehicles close to the transmitting vehicle are protected from packet retransmission.


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    Titel :

    A Creative Method for Vanet Traffic Distribution Information


    Beteiligte:

    Erscheinungsdatum :

    24.12.2022


    Anmerkungen:

    Eurasian Journal of Engineering and Technology; Vol. 13 (2022): EJET; 61-74 ; 2795-7640


    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch


    Schlagwörter :

    Klassifikation :

    DDC:    000




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