Modeling and performance analysis of VI‐CRA: A congestion control algorithm for vehicular networks

Abstract

This study proposes a Vehicle ID-based CAM Rate Adaptation (VI-CRA) algorithm for beacon messages in the vehicular network. Foremost, an improved vehicle ID-based analytical model is proposed at the MAC layer of vehicular network. The model weighs the random back-off number chosen by vehicles participating in the back-off process, with the vehicle ID incorporated in their respective CAMs. This eventually leads to the selection of a vehicle ID-based random back-off number, minimizing the probability of collision due to same back-off number selection. It is worth noting that the improved analytical model outperforms the existing works in terms of average packet delay since only one fourth of the contention window size is used throughout the simulation. To enhance the performance of the analytical model, the paper incorporates a congestion control algorithm, by adapting the rate of CAM broadcast over the control channel. The algorithm is designed considering a wide range of scenarios, ranging from nonsaturated to extremely saturated network (in terms of collision probability) and sparsely distributed to teemed network (in terms of vehicular density). For better analyses of simulation results, the algorithm is applied over different vehicle ID-based back-off numbers. Simulation results for all the back-off numbers show that vehicle ID-based CAM rate adaptation algorithm performs better than the traditional fixed CAM rate IEEE 802.11p, even at high vehicular density.