On the Comparison of Broadcasting Techniques in Vehicular Ad hoc Networks

Vehicular ad hoc Networks (VANETs) is the most great network in size which is affecting our daily life. Safety is one of the major concern in this kind of network. Autonomous communications between vehicles help to reduce traffic jam as well as accident. In one hand, the broadcasting, as a subtype of communication, is the task of sending a message to all vehicle within a predefined distance. On the other hand, alerting other vehicles can help in reducing accidents and avoiding loses. For that reason, broadcasting techniques are used in this context and it is also used to deal with other utilities like entertainment. In this paper, we perform a comparative evaluation study on the recent proposed broadcasting techniques in VANET. Three basic categories are studied (1) based on statistical method, (2) based on Deep Learning (DL), and (3) based on mixing between cloud and DL. Finally, the future trends of broadcasting techniques in VANET are discussed.