A Simulation Approach to Improve the VANETs Communication

Dublin Core

Title

A Simulation Approach to Improve the VANETs Communication

Subject

VANET, Vehicular Ad Hoc Network, Clustering, Cluster Head, Cluster Member.

Description

VANET ("vehicular ad hoc network") is a type of networks that consist of many vehicles acting as moving nodes. They are connected with other vehicles through an ad hoc wireless network so as to increase traffic security and provide relaxation to road users. Sending the messages to the final destination in VANETs is a challenging mission because of its relatively high mobility and dynamism. The clustering technique addresses such issues, as it gathers vehicles based upon several predefined metrics such us density, speed, and physical vehicles locations. Clustering in VANET is one of the controller techniques for dynamic form. In this paper, a new method is presented for clustering that suits the VANET environment with the purpose of improving the network cluster  stability. This method takes a number of parameters into consideration, such as the coverage area and speed to make the cluster structure comparatively stable. In addition, and advance is obtained in tems of the cluster-head selections algorithm, and the data exchange is improved through clusters.

Creator

Hassan, Hawraa abd Al_kadum
Zahraa Yaseen Hasan
Rusul H. Al Taie

Source

International Journal of Interactive Mobile Technologies (iJIM); Vol. 16 No. 12 (2022); pp. 137-144
1865-7923

Publisher

International Association of Online Engineering (IAOE), Vienna, Austria

Date

2022-06-21

Rights

Copyright (c) 2022 Hawraa abd Al_kadum Hassan
https://creativecommons.org/licenses/by/4.0

Relation

Format

application/pdf

Language

eng

Type

info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Non-refereed Article

Identifier

Citation

Hawraa Hassan abd Al_kadum, Zahraa Yaseen Hasan and Rusul H. Al Taie, A Simulation Approach to Improve the VANETs Communication, International Association of Online Engineering (IAOE), Vienna, Austria, 2022, accessed November 24, 2024, https://igi.indrastra.com/items/show/2317

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