Emergence of Wireless Sensor Networks provided the ability to connect, collect and disseminate information across various sensor nodes. VANETs turned out to act as a boon to enhance the safety and non-safety aspects of 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, we propose an adaptive speed based beaconing approach, which 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. We compare the results 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. We compare the results concerning generated BSMs, received BSMs and total packet loss. The simulation is modeled to make it as realistic as possible by introducing a vast heterogeneous network with random vehicle mobility trips.
Authors: Sarishma . (Assistant Professor), Ravi Tomar (University of Petroleum and Energy Studies, India), Sandeep Kumar (Sunderdeep Engineering College, Ghaziabad, India), Mukesh Awasthi (School of Physical and Decision Sciences, BBAU, Lucknow, India),
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