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A Model for the Optimization of Beacon Message Age-of-Information in a VANET
Baiocchi, Andrea; Turcanu, Ion
2017In 29th International Teletraffic Congress (ITC 29)
Peer reviewed
 

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Keywords :
Analytical models; CAM; Computational modeling; Peer-to-peer computing; Vehicular ad hoc networks
Abstract :
[en] Beaconing is a basic communication process taking place in Vehicular Ad Hoc Networks (VANETs) to achieve cooperative awareness among vehicles on the road. It is actually a paradigm of information spreading among peer-agents, where each node of a networks sends periodically broadcast messages containing information collected by the node itself. A trade-off arises between the update frequency of the broadcast information and the congestion induced in the wireless shared channel used to send the messages, which is based on the IEEE 802.11p standard in case of a VANET. For periodic updates, the primary metric is the Age-of-Information (AoI), i.e., the age of the latest update received by neighboring nodes. We define an analytical model to evaluate the AoI of a VANET, given the connectivity graph of the vehicles. Analytical results are compared to simulation to assess the accuracy of the model. The model provides a handy tool to optimize the AoI trade-off.
Disciplines :
Computer science
Author, co-author :
Baiocchi, Andrea;  Università degli Studi di Roma "La Sapienza" > Dipartimento di Ingegneria dell’Informazione, Elettronica e Telecomunicazioni (DIET)
Turcanu, Ion ;  Università degli Studi di Roma "La Sapienza" > Dipartimento di Ingegneria dell’Informazione, Elettronica e Telecomunicazioni (DIET)
External co-authors :
yes
Language :
English
Title :
A Model for the Optimization of Beacon Message Age-of-Information in a VANET
Publication date :
September 2017
Event name :
29th International Teletraffic Congress (ITC 29)
Event date :
from 04-09-2017 to 08-09-2017
Main work title :
29th International Teletraffic Congress (ITC 29)
Peer reviewed :
Peer reviewed
Commentary :
108-116 1
Available on ORBilu :
since 26 October 2017

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