CNS Core: Small: Low-Power Wide-Area Networks for Industrial Automation

CNS 核心：小型：用于工业自动化的低功耗广域网

• 批准号: 2006467
• 负责人: Abusayeed Saifullah
• 金额: $ 50万
• 依托单位: Wayne State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-10-01 至 2022-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2006467&HistoricalAwards=false
• 关键词: CNS; Core; Small; Low; Power

The evolution of Internet of Things (IoT) is transforming the field of industrial automation including process control and smart manufacturing into an important class of Industrial IoT (IIoT). Today, wireless solutions for industrial automation are based on short-range wireless technologies (e.g., WirelessHART, ISA100). To cover a large area with numerous devices, they form multi-hop mesh networks at the expense of energy, cost, and complexity, posing a big challenge to support the scale and wide-area of today’s IIoT. For example, the East Texas oil-field extends over 74x8 square kilometers requiring tens of thousands of sensors for automated management. Also, in process industries, many silos, tanks, and plants are often positioned far from the center, at inconvenient locations in difficult terrain or offshore. Pipelines can be hundreds of miles long and pass through difficult terrains, making it difficult to monitor gas and chemical leaks in real-time. This project proposes to adopt the Low-Power Wide-Area Network (LPWAN) technologies for industrial automation. Due to long-range, LPWANs can be adopted without complex configuration and at a fraction of costs for wide-area IIoT applications, compared to multi-hop solutions. This project will develop theoretical foundations and systems for enabling industrial automation using LPWANs. Its important findings will be shared with the standards bodies and industries. The developed technologies will be made open-source.This project will particularly consider LoRa, a leading LPWAN technology. Adopting LoRa for industrial automation poses some evolutionary challenges. The fundamental building blocks of any industrial automation system are feedback control loops that largely rely on real-time communication. Due to severe energy-constraints, LoRa uses a simple media access control protocol that is unsuited for real-time communication. It needs to adopt low duty-cycling in several regions (e.g., Europe). In addition, to optimize performance, industrial automation needs a codesign of real-time scheduling and control. Such a codesign becomes specially challenging in LoRa because it is large-scale and has energy-limitations. This project will address these challenges and make the following contributions: (1) an autonomous real-time scheduling technique and analysis using the demand bound function theory for LoRa; (2) a scalable scheduling-control codesign that jointly and dynamically determines control input and sampling rates; (3) a highly energy-efficient codesign by maximizing the sleeping times of the devices through a combination of self-triggered and even-triggered control adopting state-aware communication; and (4) an evaluation of the results through experiments using industrial process control use-cases on a physical testbed.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.

物联网（IoT）的发展正在将包括过程控制和智能制造在内的工业自动化领域转变为工业物联网（IIoT）的重要类别。今天，工业自动化的无线解决方案基于短距离无线技术（例如，WirelessHART, ISA100）。为了用众多设备覆盖大面积，它们以能源、成本和复杂性为代价形成多跳网状网络，这对支持当今工业物联网的规模和广域构成了巨大挑战。例如，东德克萨斯油田面积超过74x8平方公里，需要数万个传感器进行自动化管理。此外，在过程工业中，许多筒仓、储罐和设备通常远离中心，位于地形复杂或海上的不方便位置。管道可能长达数百英里，并且会穿过复杂的地形，这使得实时监测天然气和化学品泄漏变得困难。本项目提出采用低功耗广域网（LPWAN）技术实现工业自动化。由于远距离，与多跳解决方案相比，lpwan可以在没有复杂配置的情况下采用，并且在广域IIoT应用中成本很低。该项目将开发利用lpwan实现工业自动化的理论基础和系统。它的重要发现将与标准组织和行业共享。已开发的技术将实现开源。该项目将特别考虑LoRa，一种领先的LPWAN技术。在工业自动化中采用LoRa会带来一些进化上的挑战。任何工业自动化系统的基本组成部分都是主要依赖于实时通信的反馈控制回路。由于严重的能量限制，LoRa使用简单的媒体访问控制协议，不适合实时通信。它需要在几个地区（如欧洲）采用低占空比。此外，为了优化性能，工业自动化需要实时调度和控制的协同设计。这种协同设计在LoRa中变得特别具有挑战性，因为它是大规模的，并且具有能量限制。本项目将解决这些挑战，并做出以下贡献：(1)基于需求约束函数理论的LoRa自主实时调度技术和分析；(2)一个可扩展的调度控制协同设计，该协同设计共同动态地确定控制输入和采样率；(3)通过采用状态感知通信的自触发和均匀触发控制相结合，最大限度地提高设备的睡眠时间，实现高能效协同设计；(4)利用工业过程控制用例在物理测试台上进行实验，对实验结果进行评价。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。

项目成果

A Distributed Real-time Scheduling System for Industrial Wireless Networks

• DOI: 10.1145/3464429
• 发表时间: 2021-07
• 期刊: ACM Transactions on Embedded Computing Systems (TECS)
• 作者: V. P. Modekurthy;Abusayeed Saifullah;S. Madria

Low-Latency In-Band Integration of Multiple Low-Power Wide-Area Networks

多个低功耗广域网的低延迟带内集成

• DOI: 10.1109/rtas52030.2021.00034
• 发表时间: 2021
• 期刊: 2021 IEEE 27th Real-Time and Embedded Technology and Applications Symposium (RTAS
• 作者: Modekurthy, Venkata P.;Ismail, Dali;Rahman, Mahbubur;Saifullah, Abusayeed
• 通讯作者: Saifullah, Abusayeed