An Altruistic Prediction-Based Congestion Control for Strict Beaconing Requirements in Urban VANETs

Sofiane Zemouri, Soufiene Djahel, John Murphy

Research output: Contribution to journalArticlepeer-review

26 Citations (Scopus)


Periodic beacon messages are one of the building blocks that enable the operation of vehicular ad hoc networks (VANETs) applications. In vehicular networks environments, congestion and awareness control mechanisms are key for a reliable and efficient functioning of vehicular applications. In order to control the channel load, a reliable mechanism allowing real-time measurements of parameters like the local density of vehicles is a must. These measurements can then serve as an input to perform a fast adaptation of the transmit parameters. In this paper, considerable efforts have been directed in the recent years toward designing flexible yet robust protocols solving this problem; yet, very few have considered a proactive adaptation of the transmit parameters as a preventive measure from channel load peaks. To this end, we take the opportunity to introduce prediction and adaptation algorithm (PA-A), a new congestion control protocol that performs a joint adaptation of the transmit rate and power, relying on an altruistic short-term prediction algorithm that estimates the vehicular density around a given vehicle within the next short while. Additionally, PA-A adapts the transmit parameters in a way that guarantees the strict beaconing requirements and satisfies the level of awareness required for the operation of most critical VANET applications. The results of the simulations performed in a realistic scenario justify our theoretical considerations and confirm the efficiency and the effectiveness of our protocol by showing significant improvements in terms of network performance (up to 8% and 14% improvement in collision rate; and up to 10% and 20% increase in busy ratio compared to our previous scheme and the ETSI schemes, respectively) as well as the achieved level of awareness (higher coverage with higher transmission rate and power in dense scenarios, and up to 8% and 55% improvement in density perception accuracy compared to our previous scheme and the ETSI schemes, respectively).

Original languageEnglish
Article number8269413
Pages (from-to)2582-2597
Number of pages16
JournalIEEE Transactions on Systems, Man, and Cybernetics: Systems
Issue number12
Early online date19 Nov 2019
Publication statusPublished - 1 Dec 2019
Externally publishedYes


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