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车辆自组织网络(VANET)为车辆提供公平、高效的数据传输。针对密集高速移动场景,提出一种自适应门限的指数增加线性减小MAC层退避算法(A-EInLD)改善其数据冲突问题,提高系统性能。通过动态记录并更新每次成功发送时窗口的平均值并与获取的邻居节点窗口值进行比较得出竞争窗口的门限值,成功发送时基于该门限值通过连接数目对数值线性减小窗口大小从而避免冲突。最后,应用二维马尔科夫链模型分析算法并通过仿真评价性能结果。
Vehicle Self-Organizing Network (VANET) provides vehicles with fair and efficient data transmission. Aiming at the dense high-speed mobile scenario, an adaptive threshold exponential increase linear reduction MAC layer backoff algorithm (A-EInLD) is proposed to improve its data conflict and improve system performance. By dynamically recording and updating the average value of each successful sending window and comparing with the acquired neighbor node window value, the threshold value of the contention window is obtained, and based on the threshold value, the threshold of the contention window is linearly reduced by the number of connections based on the threshold value Size to avoid conflicts. Finally, the 2D Markov chain model analysis algorithm is applied and the performance results are evaluated by simulation.