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

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 (P 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).