A Mobility Prediction Based Beacon Rate Adaptation Scheme in VANETs

Abstract

In vehicular ad hoc networks, it is common for vehicles to inform their current moving states which include a vehicle's position, velocity and moving direction to their neighbors by using beacon messages periodically. However, high frequency of beacon broadcasting may lead to heavy channel load and congestion in certain scenarios. In this paper, a mobility prediction based beacon rate adaptation (MPBR) scheme is proposed to decrease beacon frequency and alleviate bandwidth consumption. By tracking their neighbors using the predicted moving states instead of using periodic beacon broadcasting, vehicles decrease the beacon rate significantly. Whenthe prediction error is higher than the threshold due to accumulation of tiny errors, a beacon broadcasting will be triggered. In order to further reduce the channel load and congestion,we classify the road traffic status into three categories to determine the value of error threshold. The simulation results clearly demonstrate the efficiency of our proposed approach.