WiFiUS: Collaborative Research: Scalable Edge Architecture for Massive Location-Aware Heterogeneous IoT Systems

面向海量位置感知异构物联网系统的可扩展边缘架构项目旨在解决在高带宽和低带宽环境下开发网络设计和物联网(IoT)系统的基本研究问题。通过定义高效的安全和可扩展性增强型边缘架构，使数据处理更接近用户，它最大限度地减少了网络中的数据传输延迟和开销。融合来自不同来源的传感器数据可以显著提高许多现有系统的效率。在一些地区，毫米波频段的蜂窝和WiFi网络即将获得大量带宽。联邦政府最近开放了高于24 GHz的28 GHz频率，并承诺彻底改变无线系统，使物联网应用成为前所未有的应用，特别是在人口稠密的城市地区。智能交通和联网(自动)汽车是新带宽实现的一个示例应用领域，这需要在大规模物联网系统的架构设计中结合这些不同的方法。将物联网与边缘/雾化计算、毫米波(毫米波)技术和分布式处理相结合，可以优化系统级性能，同时考虑到系统容量、减少数据和控制流量的网络带宽、提高系统级可编程性和自动化、精确位置感知、虚拟化、低延迟、可扩展性以及增强的安全性和私密性。我们提出的系统的一个创新方面是，它可以从模拟和模拟的环境无缝过渡到实际的生产部署，以及这些模式的混合，从而促进了强大而可靠的物联网系统的规模。该项目在物联网网络体系结构和安全的几个基本领域做出了贡献：1)最大限度地减少了大规模物联网网络中的手动配置需求；2)可扩展的认证和密钥管理系统；3)高效的分布式物联网体系结构，以执行复杂和延迟敏感的任务，并具有快速部署和原型；4)异构物联网设备之间的安全互操作性；以及5)基于毫米波通信的定位和容量优化，特别是考虑到智能交通和车载通信。该项目提出了一种在模拟和仿真中扩展物联网系统的多层方法，允许将物理系统与仿真系统相结合，将新的毫米波射频和网络模型、网络仿真、虚拟系统、物理世界的模型和用户界面结合在一起。该仿真系统允许团队探索移动边缘和雾化计算，以提高效率、减少控制环路延迟并确保敏感数据的隐私。新的身份验证模型和命名系统允许针对部署和编程进行扩展。项目中开发的原型开源物联网仿真器以及毫米波通道模型将允许工业物联网系统开发人员更快、更可靠地开发新的物联网系统。认证和命名组件将被提交以供可能的标准化。新的信道模型可能会为国家监管机构为毫米波频段的频谱分配决策提供信息。

The "Scalable Edge Architecture for Massive Location-Aware Heterogeneous IoT Systems" projectaddresses essential research problems for developing network design and Internet of Things (IoT)systems in both high bandwidth and low bandwidth environments. By defining an efficient securityand scalability-enhancing edge architecture that moves data processing close to users, it minimizesdata transfer latencies and overhead in the network. The fusion of sensor data from different sourcescan significantly improve the efficiency of many existing systems. In some areas, massivebandwidth is about to become available to cellular and WiFi networks in the millimeter wave bands.The Federal Government recently opened up 28 GHz at frequencies above 24GHz and promises to revolutionize wireless systems and enable IoT applications never beforeconceived, particularly in dense urban areas. Smart traffic and connected (autonomous) cars are anexample application area enabled by the new bandwidth, which requires combining these differentapproaches in the architectural design of large-scale IoT systems. Integrating IoT with edge/fogcomputing, millimeter wave (mmWave) technologies and distributed processing enables optimizingthe system level performance considering system capacity, reduced network bandwidth for data andcontrol traffic, increased system level programmability and automation, accurate location-aawareness,virtualization, low latency, scalability, and enhanced security and privacy. One of thenovel aspects of our proposed system is that it transitions seamlessly from an emulated andsimulated environment to actual production deployment, and mixtures of these modes, facilitatingrobust and reliable IoT systems at scale.The project provides contributions in several essential areas of IoT network architectures andsecurity: 1) minimizing the need of manual configuration in large-scale IoT networks; 2) scalableauthentication and key management systems; 3) efficient distributed IoT architecture to performcomplex and delay-sensitive tasks, with rapid deployment and prototyping; 4) secureinteroperability between heterogeneous IoT devices; and 5) positioning and capacity optimizationbased on mmWave communications, considering especially smart traffic and vehicle-to-vehiclecommunications. The project proposes a multi-layered approach for scaling IoT systems insimulation and emulation, allowing to combine physical systems with emulated systems,incorporating new mmWave RF and network models, network emulation, virtual systems, modelsof the physical world and user interfaces. The emulation system allows the team to explore mobileedge and fog computing to enhance efficiency, reduce control-loop delays and assure privacy ofsensitive data. A new authentication model and naming system allows scaling for deployment andprogramming. The prototype open-source IoT emulator, along with the mmWave channel models,developed in the project will allow industrial IoT system developers to more rapidly and reliablydevelop new IoT systems. The authentication and naming components will be submitted forpossible standardization. The new channel models are likely to inform spectrum allocationdecisions for mmWave bands by national regulators.