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

CNS 核心：小型：为机器人提供 5G 服务的软件定义方法

• 批准号: 1910150
• 负责人: Songwu Lu
• 金额: $ 40万
• 依托单位: University of California-Los Angeles
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-10-01 至 2023-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1910150&HistoricalAwards=false
• 关键词: CNS; Core; Small; Software; Defined

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.

第一部分：5G基础设施全球部署正在进行中。这项即将推出的技术预计将支持当今数十亿的移动用户和未来数万亿的互联事物。机器人应用是5G的一类新兴应用，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对其软件堆栈（以协议的形式）进行5G技术创新。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，从我们的初步结果来看，这也是一条同样重要的途径。我们力求实现三个目标。首先，我们从设备端完善了 5G 软件堆栈，以实现标准内的低延迟。其次，我们通过以设备为中心的软件技术确保5G系统的高可靠性。第三，我们为 5G 设备提供新的学习和推理功能，适用于常见的使用设置和容易出现故障的场景。如果成功，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培训和准备下一代 5G 技术劳动力。第二部分：拟议的研究具有三个关键的技术贡献领域。首先，我们使用机器人应用程序来推动以设备为中心的 5G 创新。它量化了低延迟和高可靠性的要求，为针对应用程序定制的软件定义的可靠性和延迟提供了案例，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状态副本，并优化控制平面和数据平面上的 5G 延迟。为了提高可靠性，我们利用并发网络访问（通过连接到两个基站和每个基站的多个并发无线通道）和检测和反应来提高可靠性。我们利用现有的 5G 机制和最新的检查点方案，设计了新颖的主动故障屏蔽和被动恢复组件。我们根据应用的可靠性要求进一步调整各种调谐旋钮。第三，我们在设备上提供新的学习和推理功能，以开放封闭的 5G 网络运营，并使应用程序能够进一步适应。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Data-plane signaling in cellular IoT: attacks and defense

• DOI: 10.1145/3447993.3483255
• 发表时间: 2021-10
• 期刊: Proceedings of the 27th Annual International Conference on Mobile Computing and Networking
• 作者: Zhaowei Tan;Boyan Ding;Jinghao Zhao;Yunqi Guo;Songwu Lu

Device-Centric Detection and Mitigation of Diameter Signaling Attacks against Mobile Core

以设备为中心的针对移动核心的 Diameter 信令攻击检测和缓解

• DOI: 10.1109/cns53000.2021.9705031
• 发表时间: 2021
• 期刊: Proceedings of 2021 IEEE Conference on Communications and Network Security (CNS
• 作者: Tan, Zhaowei;Ding, Boyan;Zhang, Zhehui;Li, Qianru;Guo, Yunqi;Lu, Songwu
• 通讯作者: Lu, Songwu

LDRP: Device-Centric Latency Diagnostic and Reduction for Cellular Networks Without Root

• DOI: 10.1109/tmc.2023.3267805
• 发表时间: 2024-04
• 期刊: IEEE Transactions on Mobile Computing
• 影响因子: 7.9
• 作者: Zhaowei Tan;Jinghao Zhao;Yuanjie Li;Yifei Xu;Yunqi Guo;Songwu Lu

5G Messaging: System Insecurity and Defenses

5G 消息传递：系统不安全性和防御

• DOI: 10.1109/cns56114.2022.9947238
• 发表时间: 2022
• 期刊: Proceedings of 2022 IEEE Conference on Communications and Network Security (CNS
• 作者: Zhao, Jinghao;Li, Qianru;Yuan, Zengwen;Zhang, Zhehui;Lu, Songwu
• 通讯作者: Lu, Songwu

SEED: a SIM-based solution to 5G failures

• DOI: 10.1145/3544216.3544260
• 发表时间: 2022-08
• 期刊: Proceedings of the ACM SIGCOMM 2022 Conference
• 作者: Jinghao Zhao;Zhaowei Tan;Yifei Xu;Zhehui Zhang;Songwu Lu