2015
DOI: 10.1016/j.comcom.2015.01.017
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RTAD: A real-time adaptive dissemination system for VANETs

Abstract: Efficient message dissemination is of utmost importance to propel the development of useful services and applications in Vehicular ad hoc Networks (VANETs).In this paper, we propose a novel adaptive system that allows each vehicle to automatically adopt the optimal dissemination scheme in order to fit the warning message delivery policy to each specific situation. Our mechanism uses as input parameters the vehicular density and the topological characteristics of the environment where the vehicles are located, … Show more

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Cited by 43 publications
(25 citation statements)
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“…The proposed NJL scheme not only increases the percentage of informed vehicles through message broadcast technique but also reduced the number of messages up to 46.73% [27]. Other similar works studied include the further research carried out by Sanguesa et al [28], a Real-Time Adaptive Dissemination (RTAD) scheme for VANETs, two distinct protocols in [29], TRAck DEtection (TRADE) and Distance Defer Transmission (DDT) protocols, Optimized Dissemination of Alarm Messages (ODAM) [30], Smart Broadcast Algorithm (SBA) [31], Contention Based Dissemination (CBD) [32], Time Reservation-based Relay Node Selecting Algorithm (TRRS) and Enhanced TRRS (ETRRS) [33], Urban Multi-hop Protocol (UMB) [34], BROADCOMM [35], Fast Broadcast (FB) protocol [36], and REAR [37]. In Table IV …”
Section: Message Broadcasting In Vanetmentioning
confidence: 89%
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“…The proposed NJL scheme not only increases the percentage of informed vehicles through message broadcast technique but also reduced the number of messages up to 46.73% [27]. Other similar works studied include the further research carried out by Sanguesa et al [28], a Real-Time Adaptive Dissemination (RTAD) scheme for VANETs, two distinct protocols in [29], TRAck DEtection (TRADE) and Distance Defer Transmission (DDT) protocols, Optimized Dissemination of Alarm Messages (ODAM) [30], Smart Broadcast Algorithm (SBA) [31], Contention Based Dissemination (CBD) [32], Time Reservation-based Relay Node Selecting Algorithm (TRRS) and Enhanced TRRS (ETRRS) [33], Urban Multi-hop Protocol (UMB) [34], BROADCOMM [35], Fast Broadcast (FB) protocol [36], and REAR [37]. In Table IV …”
Section: Message Broadcasting In Vanetmentioning
confidence: 89%
“…Besides, homogeneous vehicular traffic densities are common in one-dimensional highways as opposed to two-dimensional urban vehicular scenarios [70]. Interestingly, as opposed to most of the works compared in Table VI [26][27][28][29][ 56-65, 68, 70], the works of Fogue et al [26], Sanguesa et al [27] and Martinez et al [37] carried out a simulation of real city maps with buildings using a modified NS-2 simulator to model the impact of distance and obstacles in signal propagation. The wireless Radio Propagation Model used is the Real Attenuation and Visibility Model (RAV) [37] [71], a model which proved to increase the level of realism in VANET simulations using real-life urban roadmaps as scenarios where buildings act as obstacles.…”
Section: Congestion Control Techniques In Inter-vehicle Communicationmentioning
confidence: 93%
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“…Although proposed for MANETs, the idea of social preferences may be applied to VANETs to improve content distribution solutions. RTAD [Sanguesa et al 2015] is a real-time adaptive dissemination system in which vehicles decide the broadcast scheme to use, among a set of schemes, based on the current network density and topology information on the road. Thus, this solution is expected to perform well under different network conditions.…”
Section: Push-based Solutionsmentioning
confidence: 99%
“…To distribute the security related information in VANETs the best possible way is to broadcast the message. Flooding of message is an easiest way to distribute the information [6] [7]. With the help of Flooding technique the security related messages will be transmitted again by the vehicles and this will be received by all neighboring vehicles.…”
Section: Introductionmentioning
confidence: 99%