Auto-Adaptive Multi-Hop Clustering for Hybrid Cellular-Vehicular Networks - Archive ouverte HAL Access content directly
Conference Papers Year : 2017

Auto-Adaptive Multi-Hop Clustering for Hybrid Cellular-Vehicular Networks

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

Abstract

In this paper, we consider a hybrid vehicular network, in which vehicles transmit data via the cellular network and dispose of a V2V interface. In this context, we propose an auto-adaptive multi-hop clustering algorithm, which optimizes the cellular radio resource under the constraint of a maximum packet loss rate (PLR) in the V2V network. The larger V2V based clusters are, the higher the data compression ratio at the cluster head is and the smaller the amount of required resource on the cellular link is. However, PLR becomes higher due to the collision on the V2V channel when increasing the number of hops. The proposed algorithm thus adapts dynamically the maximum number of hops in clusters according to the vehicular traffic density. By simulations, we show that it performs better in terms of aggregated cellular data and packet loss rate than any fixed-hop clustering algorithm in a dynamic scenario.
Not file

Dates and versions

hal-02288490 , version 1 (14-09-2019)

Identifiers

  • HAL Id : hal-02288490 , version 1

Cite

Julian Garbiso, Ada Diaconescu, Marceau Coupechoux, Bertrand Leroy. Auto-Adaptive Multi-Hop Clustering for Hybrid Cellular-Vehicular Networks. IEEE International Conference on Intelligent Transportation Systems (ITSC), Oct 2017, Yokohama, Japan. pp.1-6. ⟨hal-02288490⟩
29 View
0 Download

Share

Gmail Facebook Twitter LinkedIn More