Data Forwarding Techniques Based on Graph Theory Metrics in Vehicular Social Networks - Archive ouverte HAL Access content directly
Conference Papers Year :

Data Forwarding Techniques Based on Graph Theory Metrics in Vehicular Social Networks

(1) , (2) , (3)
1
2
3

Abstract

Intelligent inter-vehicle communication is a key research field in the context of vehicular networks that applies in real-life applications (e.g., management of accidents, intelligent fuel consumption, smart traffic jams, etc.). Considering different roles of nodes based on their " social aptitude " to relay information could provide a social component in the vehicular structure that can be useful in getting a clear prediction of the topological evolution in time and space proving to be very effective in managing intelligent data forwarding. In this work we characterize a vehicular network as a graph using the link layer connectivity level and we classify nodes on the basis of specific attributes characterizing their " social aptitude " to forward data. Two forwarding approaches are presented, based on different socialites that allow to (i) select the most social node (i.e., a social hub) or (ii) choose among various social nodes.
Fichier principal
Vignette du fichier
PIMRC_conf_v2.pdf (743.3 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-01826237 , version 1 (29-06-2018)

Identifiers

  • HAL Id : hal-01826237 , version 1

Cite

Anna Maria Vegni, Valeria Loscrì, Pietro Manzoni. Data Forwarding Techniques Based on Graph Theory Metrics in Vehicular Social Networks. IEEE PIMRC 2018 - 29th Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, Sep 2018, Bologna, Italy. ⟨hal-01826237⟩

Collections

INRIA INRIA2
92 View
185 Download

Share

Gmail Facebook Twitter LinkedIn More