An Adaptive Back-Off Scheme Based on Improved Markov Model for Vehicular ad hoc Networks

In vehicular ad hoc networks (VANETs), the vehicles will periodically exchange information via broadcasting security-related message, such as the states of vehicles and roads, in which the performance may become worse when the vehicle density increases. To improve the poor performance of network when vehicular density is high, an adaptive back-off scheme based on improved Markov model is proposed in this paper. First, an improved Markov model with a contention window (
$CW$
) inheritance mechanism is applied to reduce the network load. The vehicle with the improved model will take beacon expiration into account and actively discard expired beacons to relieve the pressure on the channel. Then, an initial
$CW$
selection mechanism is designed to improve the efficiency of accessing the channel through providing the optimal initial
$CW$
for the vehicles with different densities. Finally, we define a network busy factor to describe the condition of broadcast channel and propose an adaptive back-off algorithm which can dynamically adjust the
$CW$
according to the network busy factor. Simulation results show that the new scheme can significantly improve the performance of broadcast.