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VEHICAST - Privacy‐guaranteed fast content delivery for hybrid VANETs. 

Axe : ComEx & [https://digicosme.lri.fr/tiki-
Coordinateurs : Véronique Veque, Houda Labiod
Nom & Prénom du Candidat : Sara Berri
Institutions: L2S/LTCI
Laboratoire gestionnaire: LTCI
Adossé à l'action DigiCosme : GT Future Access Networks
Durée & Dates de la mission : 1 an - 15/07/2018 - 14/07/2019

Contexte :
A variety of applications envisaged by Intelligent Transportation Systems (ITS), such as public safety, traffic management or passenger‐oriented like audio/video downloading needs either high data rate, or short transmission delay and always, seamless data connectivity. To guarantee the performance of such applications, vehicular communication are particularly required to provide high‐performance data delivery B6. One solution is the heterogeneous integration of IEEE 802.11p VANETs (Vehicular Ad hoc networks) with wide‐range 3GPP LTE systems to take both advantage of the widespread coverage of cellular networks but with erratic rates in some areas and of high‐speed rate of the 802.11 road side unit (RSU) but in limited covered areas. In R2, the authors investigate the usability of LTE to support
vehicular applications underlying the strengths and weaknesses but also open up some lines of discussion. In this project, we consider the integration of LTE‐A 4G cellular technology with IEEE 802.11p based VANET to provide high data rates and seamless connectivity to a group of vehicles. Our proposals are based on vehicular clustering R1, R4, R6, R10 which consists in logically grouping vehicles, based on similar vehicular characteristics (direction, lane, speed, etc.). This moving cluster is leaded by a clusterhead (CH) which could eventually serve as a gateway to the infrastructure for all vehicles in the cluster.

Objectif :
In this project, we target to provide easily infotainment services for ITS and it has to be carefully evaluated In terms of network traffic but also storage capacity for the server. In this problem, the considered application is to download a video or a data content which both are divided into chunks. RSUs pre‐fetch requested data chunks requested by vehicles, so that clusterheads passing along them can download data chunks via IEEE802.11 connection, which is much faster than LTE and IEEE802.11p links. The issue is to design the strategy to allocate pre‐fetched data at RSUs, or vehicles, so as to provide high coverage for vehicles that request for data. We will take into consideration of the relationship between vehicle velocity, vehicle/RSU connection time with the downloading rate from RSUs, and analyze the relationship between data pre‐fetching efficiency and privacy level. In addition, we will
study the relationship between the clustering algorithms and the performance in data fetching, by extending our previous work in R3, R5, R7, R8, R9.

Productions Scientifiques :
  • 1 Sara Berri, Jun Zhang, Brahim Bensaou, and Houda Labiod, Content-Prefeching and Broadcast Scheduling in Vehicular Networks with a Realistic Channel Model, IEEE IECCO 2019 (in conjunction with IEEE INFOCOM 2019)
  • 2 Sara Berri, Jun Zhang, Brahim Bensaou, and Houda Labiod, Joint Data-Prefetching and Broadcast-Scheduling for Hybrid Vehicular Networks, IEEE ICC 2019
  • 3 A. Mouradian, Claudia Campolo, Antonella Molinaro, A. O. Berthet, V. Vèque. “Characterizing Full-Duplex V2V Broadcast Performance through Stochastic Geometry”, IEEE Consumer Communications & Networking Conf. (CCNC), January 2019, Las Vegas,USA.
  • 4 Alexandre Mouradian, "Modeling dense urban wireless networks with 3D stochastic geometry". Performance Evaluation, 121-122: 1-17 (2018)