Local Density Estimation for VANETs

Noureddine Haouari 1, * Samira Moussaoui 1, * Mohamed Guerroumi 1, * Sidi Mohammed Senouci 2
* Auteur correspondant
1 Faculté d'Electronique et Informatique, USTHB
2 DRIVE - Département de Recherche en Ingéniérie des Véhicules pour l'Environnement
Abstract : Local vehicle density estimation is an integral part of various applications of Vehicular Ad-hoc Networks (VANETs) such as congestion control and congestion traffic estimation. Currently, many applications use beacons to estimate this density. However, many studies show that the reception rate of these beacons can significantly drop at short distances due to a broadcast storm problem in high-density situations. Therefore, the local vehicle density estimation helps VANETs' applications in giving an estimate of the number of neighbors in their communication range where a vehicle could send and receive correctly packets. Indeed, an accuracy local density estimation considerably enhances the performance of these applications and makes them adaptable to different road scenarios. Our aim in this work is to extend more the local density to be segmented and within the maximum transmission range. This potential gives VANETs' application the ability to estimate at different ranges depending on their requirements. To this goal, this paper proposes a segment-based approach that ensures high accuracy with low overhead over the maximum vehicles transmission range. Performance results show that the proposed strategy reaches a mean error ratio of approximately 3% with limited overhead over 1000m of range.
Keywords : Vehicles DH-HEMTs Estimation Roads Safety Protocols Histograms vehicular ad hoc networks broadcast storm problem local vehicle density estimation VANET applications vehicular ad-hoc network applications beacon reception rate
Type de document :
Communication dans un congrès
Global Information Infrastructure and Networking Symposium (GIIS), Oct 2016, Porto, Portugal. IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA, 2016 Global Information Infrastructure and Networking Symposium (giis), 2016, 〈http://ieeexplore.ieee.org/document/7814935/〉. 〈10.1109/GIIS.2016.7814935〉
Liste complète des métadonnées

Littérature citée [15 références]  Voir  Masquer  Télécharger
https://hal-univ-bourgogne.archives-ouvertes.fr/hal-01543398
Contributeur : Ub_drive Université de Bourgogne <>
Soumis le : samedi 24 février 2018 - 00:45:37
Dernière modification le : jeudi 14 février 2019 - 15:52:02
Document(s) archivé(s) le : vendredi 25 mai 2018 - 22:34:43

Fichier

haouari2016.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

Collections

DRIVE | TDS-MACS | UNIV-BOURGOGNE

Citation

Noureddine Haouari, Samira Moussaoui, Mohamed Guerroumi, Sidi Mohammed Senouci. Local Density Estimation for VANETs . Global Information Infrastructure and Networking Symposium (GIIS), Oct 2016, Porto, Portugal. IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA, 2016 Global Information Infrastructure and Networking Symposium (giis), 2016, 〈http://ieeexplore.ieee.org/document/7814935/〉. 〈10.1109/GIIS.2016.7814935〉. 〈hal-01543398〉

Exporter

BibTeX TEI DC DCterms EndNote

Partager

Métriques

Consultations de la notice

74

Téléchargements de fichiers

50

Contact

support.ccsd.cnrs.fr
hal.support@ccsd.cnrs.fr
Logo CCSD