The vehicular ad-hoc networks make a simple case of networks which are supposed to be very smart because of the tasks and crucial decision making they have to carry out. Since they are on the move, the transmission and reception of information has to be quick in order to make the networks
efficient in term of computing time. Fog enabled VANET make the systems more capable by processing much of the information locally and only sending crucial decision making to the cloud which saves time and worth for all sub dependent systems. In this work we have reviewed the two fog enabled
VANET schemes, one is SIVNFC (Secure intelligent vehicular network using fog computing) and the other is SOLVE (localization system frameworks).
A Machine Learning System for Routing Decision-Making in Urban Vehicular Ad Hoc Networks