NeTS: Small: VC-VANET: A Sustainable Vehicle-Crowd Based Vehicular Ad Hoc Network Supporting Mobile Cloudlet Computing

随着交通工具的不断发展，开发新的和创新的智能交通方法是国家的一个关键需求。不久之后，我们将在每个州的道路系统中看到更多的自动驾驶汽车和联网汽车。据预测，到2020年，将有大约2.5亿辆联网汽车上路。这种车辆环境，具有来自移动车辆和运输系统的通信能力，提出了一个极其庞大和复杂的移动网络场景，其中多种通信技术可用。本研究的目标是研究一个以车辆人群为中心的网络化系统，该系统具有支持高需求移动边缘计算应用的能力。其好处包括更及时和准确的数据输入和结果输出，以及作为基于基础设施的系统的替代方案。这些应用可能包括：智能交通系统应用、交通相关的计算需求、时间紧迫的情况感知应用和可视化。这项工作的成果将传播到多个学科，并用于为研究生和本科生编写教育和培训材料，并为传统上代表性不足的群体和本科生提供研究机会。提出的研究将促进对物理车辆网络和运输操作之间相互依存关系的了解，以支持高需求应用。该项目设想了通过车辆网络协议在分组车辆之间协作获取计算和存储资源来支持这些应用程序的能力。这种网络架构是分层的，因为这些联网车辆组是车辆自组织网络和单个车辆的车辆延迟容忍网络之上的额外层。本研究的独特重点将是发现与信号控制等因素相关的车辆-人群系统特性，并利用从当地城市交通系统收集的数据开发适应性车辆-人群方案，以应对不利条件。本项目的主要研究任务有三个：(1)研究单个车辆-人群的特性，即在给定的时间域中，车辆-人群在给定位置发生的动态模式，以及需要恢复时的延迟。(2)研究多车辆-人群的时空特征，以及发生的协调关系。(3)研究车辆-人群预测方法。

The development of new and innovative methods for smart transportation is a critical need of the nation as vehicles continue to evolve. Not long from now, we will see more autonomous vehicles and connected vehicles on the road systems in each state. It is predicted that by 2020 there will be approximately 250 million connected vehicles on the road. Such a vehicular environment, with communication capabilities from the moving vehicles and the transportation systems, presents an extremely large and complex mobile networking scenario where multiple communication technologies are available. The goal of this research is to investigate a vehicle-crowd centered, networked system that has the capability to support high-demand mobile edge computing applications. The benefits could range from more prompt and accurate data inputs and result outputs, to being an alternative for infrastructure-based systems. The applications could include: intelligent transportation system applications, transportation related compute-hungry, time-critical situation-aware applications, and visualizations. Results of this effort will be disseminated to multiple disciplines, and be used to develop education and training materials for both graduate and undergraduate students as well as provide research opportunity for traditionally under-represented groups and undergraduate students. The proposed research will advance the knowledge about the interdependent relationships between the physical vehicle network and the transportation operation for supporting high-demand applications. This project envisions the capability to support these applications through harvesting the computing and storage resources by collaborations among grouped vehicles which are knitted together via the vehicular networking protocols. Such a network architecture is hierarchical as these groups of connected vehicles are an additional layer on top of vehicle ad hoc networks and vehicle delay tolerant networks of individual vehicles. The unique emphasis of this research will be finding the vehicle-crowd system properties relating to signal control among other factors, and developing adaptive vehicle-crowd schemes in reacting to adverse conditions using data collected from local city transportation systems. This project focuses on three main research tasks: (1) Investigate the properties of an individual vehicle-crowd, namely, the dynamic patterns of its occurrence at a given location in the time domain, and the latency when recovery is desired. (2) Investigate the spatial and temporal properties relating to multiple vehicle-crowds, and how the occurrences coordinate. (3) Investigate prediction methods to help sustain the vehicle-crowds.