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

随着车辆的不断发展，开发新的和创新的智能交通方法是国家的迫切需要。不久之后，我们将在每个州的道路系统上看到更多的自动驾驶汽车和联网汽车。据预测，到2020年，道路上将有大约2.5亿辆联网汽车。这样的车载环境具有来自移动车辆和运输系统的通信能力，呈现了一个非常大且复杂的移动联网场景，其中多种通信技术可用。本研究的目标是研究一种能够支持高需求移动边缘计算应用的以车辆人群为中心的网络化系统。好处可能从更迅速、更准确的数据输入和结果输出，到成为基于基础设施的系统的替代方案。这些应用程序可能包括：智能交通系统应用程序、与交通相关的计算密集型、时间关键型情况感知应用程序和可视化应用程序。这一努力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交通运营之间相互依赖关系的认识，以支持高需求的应用。该项目设想了通过分组车辆之间的协作来获取计算和存储资源以支持这些应用的能力，这些车辆通过车载网络协议被编织在一起。这种网络体系结构是分层的，因为这些连接的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附加层。这项研究的唯一重点将是找出与信号控制等因素有关的车辆-人群系统特性，并利用从当地城市交通系统收集的数据来开发适应不利条件的车辆-人群方案。本课题主要集中在三个方面的研究工作：(1)研究单个车辆-人群的特性，即其在时间域中某一给定位置的动态出现模式，以及期望恢复时的延迟。(2)研究与多车群相关的空间和时间特性，以及各事件如何协调。(3)研究预测方法，以帮助维持车辆拥堵。

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.