With the rapid evolution of Wi-Fi technology and the dramatic increase in Wi-Fi coverage, it has become lot more convenient to transfer data by using roadside AP (Access Point). Previous research has proved the feasibility of using vehicular Wi-Fi infrastructure to deliver data packages. However, the issue of optimization of the AP's selection method under different mobility patterns is still open to research. To tackle this issue, this paper proposes an AP selection scheme that maximizes the potential connection time by using Received Signal Strength Indication (RSSI) to predict the duration of future connection between the specific vehicle and APs. Choosing APs with maximum connection duration guarantees the reduction of disconnection rate and packet loss, while improving the stability of the data traffic. The experimental results show that our strategy improves the average connection time and reduces the number of handovers, thereby significantly enhancing communication quality.
车载网络通过移动车辆的无线通信装置实现数据共享,是未来智能交通系统中的重要技术。传统的车载网络数据分发大多基于泛洪的传染扩散方法,其虽能适应网络的拓扑动态性,却无法达到高效和实用的目的。提出了一种适用于车载机会网络的自适应拷贝数据分发算法ACS(Adaptive Copy and Spreading),它通过车辆移动参数(如方向、速度)动态计算所需分发数据的拷贝数并确定消息删除策略。仿真结果表明,ACS算法相比随机选择分发算法和传染扩散算法降低了对网络资源的需求,适用于多种应用场景。
