CNS Core: Small: A Software-Defined Approach to 5G Services for Robots

第一部分：5G基础设施的全球部署正在进行中。这项即将到来的技术预计将支持今天数十亿的移动用户和未来数万亿的联网设备。机器人应用是5G的新一类新兴应用，但对低延迟、高可靠性和高速度提出了严格的要求。在这个项目中，我们建议从设备端而不是基础设施内部在其软件堆栈（以协议的形式）中创新5G技术。我们使用展示机器人应用程序来推动我们的设计工作。我们挑战了传统观念，即无线接入是实现低延迟和高可靠性的唯一障碍。相反，我们从设备的角度来看待5G软件创新，这是我们最初结果的一个同样重要的途径。我们力求实现三个目标。首先，我们从设备端完善5G的软件堆栈，以实现标准内的低延迟。其次，我们通过5G系统上以设备为中心的软件技术确保高可靠性。第三，我们为5G设备提供了新的学习和推理能力，既适用于常见的使用设置，也适用于容易发生故障的场景。如果成功，它可能有助于推进机器人在我们日常生活和社会中的应用。该提案进一步有助于为5G技术培训和准备下一代劳动力。第二部分：提出的研究有三个关键的技术贡献领域。首先，我们使用机器人应用来推动我们以设备为中心的5G创新。它量化了对低延迟和高可靠性的需求，为软件定义的可靠性和适合应用程序的延迟提供了一个案例，并提供了评估设计的基准。其次，我们采用以设备为中心的方法来实现高可靠性和低延迟。我们的解决方案在设计时利用了状态副本，并优化了控制平面和数据平面的5G延迟。为了提高可靠性，我们利用了并发网络访问（通过连接到两个基站和多个并发无线通道到每个基站）和检测和反应来提高可靠性。通过利用现有的5G机制和最新的检查点方案，我们设计了新的主动故障屏蔽和响应式恢复组件。我们进一步调整各种调优旋钮以满足应用程序的可靠性要求。第三，我们在设备上提供新的学习和推理功能，打开封闭的5G网络运营，使应用程序能够进一步适应。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Part I:The global deployment of the 5G infrastructure is underway. This upcoming technology is envisioned to support billions of mobile users today and trillions of connected things tomorrow. Robotic applications are a new class of emerging applications for 5G, yet posing stringent requirements on low latency, high reliability, and high speed. In this project, we propose to innovate the 5G technology in its software stack (in the form of protocols) from the device side rather than inside the infrastructure. We use showcase robotic applications to drive our design effort. We challenge the conventional wisdom that wireless access is the sole roadblock for low latency and high reliability. Instead, we take the device perspective on 5G software innovation, which poses as an equally critical pathway from our initial results. We seek to achieve three goals. First, we refine the software stack of 5G for low latency within the standards from the device side. Second, we ensure high reliability through device-centric software techniques on the 5G system. Third, we provision 5G devices with new capabilities of both learning and reasoning for both common usage settings and failure-prone scenarios. If successful, it may help to advance robotic applications in our daily life and the society. The proposal further helps to train and prepare the next-generation workforce for 5G technology.Part II:The proposed research has three key areas of technical contributions. First, we use the robotic applications to drive our device-centric 5G innovations. It quantifies the requirements on low latency and high reliability, makes a case for software-defined reliability and latency tailored to applications, and offers benchmarks for assessing the design. Second, we take the device-centric approach to high reliability and low latency. Our solution leverages the state replica at the design and optimizes 5G latency on both control and data planes. To improve reliability, we exploit both concurrent network access (via connectivity to two base stations and multiple concurrent wireless channels to each) and detect-and-react for higher reliability. We devise novel proactive failure masking and reactive recovery components, by leveraging existing 5G mechanisms and recent checkpointing schemes. We further adjust various tuning knobs to the application's reliability requirement. Third, we provide new learning and reasoning functions at the device to open up the closed 5G network operations and enable the applications for further adaptations.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.