NeTS: Small: SOAR: Leveraging Traffic Signatures to Improve Performance of Vehicular Networks

车联网是车辆安全通信、远程车辆诊断、网络辅助自动驾驶等下一代交通服务的使能技术。支持这些应用的一个主要挑战是在存在噪声、干扰和移动引起的无线信道变化的情况下，利用有限的无线网络频谱资源实现实时、可靠的通信。该项目开发了一种新的跨层框架，可以在不产生额外频谱开销的情况下提高车载网络的性能。关键的观察结果是，由于特定于协议的报头结构和应用数据的时空相关性，流量通常表现出很高的可预测性，例如车辆位置、车载传感器读数和到周围对象的距离。该项目采用系统方法来利用这种流量特征来优化车辆网络性能。该方法基于自上而下的跨层结构，包括：1)在网络流量的动态变化下保证准确率的流量特征提取算法；2)提高对信道变化和干扰的稳健性和抗干扰能力的流量特征感知PHY算法；3)综合链路层，利用流量特征对功率控制、速率自适应和差错恢复进行细粒度优化。该项目对未来多个应用领域的车载网络系统具有广泛的意义，这些应用领域在频谱资源受限的情况下对通信可靠性要求很高。该解决方案框架对车载网络应用是透明的，可以与各种无线标准集成，包括802.11p、WiMAX和LTE，以便在车辆间和车辆到基础设施网络中提供更好的服务质量(Qos)。教育和外联活动包括将车辆网络系统引入新的研究生课程，并在项目过程中开发软件、试验床和实验室，以及招募妇女和少数族裔学生参与该项目。

Vehicular networking is an enabling technology for the next-generation transportation services, such as vehicle safety communication, remote vehicle diagnosis, and network-assisted autonomous driving. A major challenge to support these applications is to achieve real-time, reliable communication using limited wireless network spectrum resource, in the presence of noise, interference, and mobility-induced wireless channel variations. This project develops a novel cross-layer framework that improves the performance of vehicular networks without incurring extra spectrum overhead. The key observation is that traffic typically exhibits high predictability due to protocol-specific header structures and the spatiotemporal correlation of application data, such as vehicle positions, on-board sensor readings, and the range to surrounding objects. This project takes a system approach to leveraging such traffic signatures to optimize vehicular network performance. The approach is based on a top-down cross-layer architecture, which consists of 1) a traffic signature extraction algorithm that achieves assured accuracy under the dynamics of network traffic; 2) traffic signature-aware PHY algorithms that improve the robustness and resilience to channel variations and interference; and 3) a comprehensive link layer that exploits traffic signatures in fine-grained optimization of power control, rate adaptation and error recovery.This project has broad implications for future vehicular network systems in multiple application domains that demand high communication reliability under spectrum resource constraints. The solution framework is transparent to vehicular network applications and can be integrated with various wireless standards, including 802.11p, WiMAX and LTE, for providing better Quality of Service (QoS) in both inter-vehicle and vehicle-to-infrastructure networks. Educational and outreach activities include introduction of vehicular network systems into new graduate courses with software, testbed, and labs developed in the course of this project, and recruitment of women and minority students for participation in the project.