To Beacon or Not?: Speed Based Probabilistic Adaptive Beaconing Approach for Vehicular Ad-Hoc Networks

Abstract

Emergence of Wireless Sensor Networks provided the ability to connect, collect and disseminate information across various sensor nodes. Deploying this concept in the transportation domain evolved into the concept of Vehicular Ad-hoc Sensor Networks (VASNETs) or Vehicular Ad-hoc Networks (VANETs). VANETs turned out to act as a boon to enhance the safety and non-safety aspects of the transportation domain, giving way to the future of Intelligent Transport Systems. To generate cooperative awareness in the network, VANETs use beacons, which are small packets of information transmitted as BSMs (Basic Safety Messages). Beaconing was developed in the initial phases of development of VANETs and mainly suffers a trade-off between channel congestion and the level of accuracy of exchanged information. In this work, an adaptive speed based beaconing approach is proposed, the approach uses probability as a means to answer two key questions. First is whether to beacon or not and second is at what rate beaconing should be done to reduce channel congestion and increase the accuracy of information. The results are compared with an adaptive density-based approach and with normal static beaconing cases. Performance evaluation on Veins framework demonstrates that it gives better results as compared to both the other approaches. Further, the results concerning generated BSMs, received BSMs and total packet loss are compared. The simulation is modeled to make it as realistic as possible by introducing a vast heterogeneous network with random vehicle mobility trips.