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: 2301757
• 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: 2022
• 资助国家: 美国
• 起止时间: 2022-10-01 至 2024-10-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2301757&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) 的发展正在将过程控制和智能制造等工业自动化领域转变为工业物联网 (IIoT) 的重要类别。如今，工业自动化的无线解决方案基于短程无线技术（例如，无线技术）。 、WirelessHART、ISA100），为了覆盖大量设备的大面积，它们形成多跳网状网络，代价是能源、成本和复杂性，这对支持当今工业物联网的规模和广域提出了巨大的挑战。 。 例子，东德克萨斯油田面积超过 74x8 平方公里，需要数以万计的传感器进行自动化管理。此外，在流程工业中，许多筒仓、储罐和工厂通常远离中心，位于地形复杂或近海的不方便位置。管道可能长达数百英里并穿过复杂的地形，因此很难实时监控天然气和化学品泄漏。该项目建议采用低功耗广域网（LPWAN）技术进行工业自动化。与多跳解决方案相比，长距离、低功耗广域网无需复杂的配置即可采用，并且成本低廉，该项目将开发使用低功耗广域网实现工业自动化的理论基础和系统。开发的技术将开源。该项目将特别考虑 LoRa，这是一种领先的 LPWAN 技术，采用 LoRa 进行工业自动化会带来一些革命性的挑战。由于严格的能量限制，LoRa使用不适合实时通信的简单媒体访问控制协议，需要在多个区域采用低占空比。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源限制。挑战并做出以下贡献：(1) 使用 LoRa 的需求约束函数理论的自主实时调度技术和分析；(2) 联合动态确定控制输入和采样率的可扩展调度控制代码； - 通过采用状态感知通信的自触发和偶触发控制相结合来最大化设备的休眠时间，从而实现高效的代码设计；(4) 通过在物理上使用工业过程控制用例进行实验来评估结果；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

Precise Scheduling of DAG Tasks with Dynamic Power Management

通过动态电源管理精确调度 DAG 任务

• 发表时间: 2023-07
• 期刊: Leibniz international proceedings in informatics
• 作者: Bhuiyan; Ashikahmed and
• 通讯作者: Ashikahmed and

Towards Mixed Criticality Industrial Wireless Sensor-Actuator Network

迈向混合关键工业无线传感器执行器网络

• DOI: 10.1145/3571306.3571447
• 发表时间: 2023-01-04
• 期刊: Proceedings of the 24th International Conference on Distributed Computing and Networking
• 作者: Prashant Modekurthy;Mahbubur Rahman
• 通讯作者: Mahbubur Rahman

Energy- and Temperature-aware Scheduling: From Theory to an Implementation on Intel Processor

能源和温度感知调度：从理论到英特尔处理器上的实现

• DOI: 10.1109/hpcc-dss-smartcity-dependsys57074.2022.00288
• 发表时间: 2022-12
• 期刊: ICESS 2022 (the 18th IEEE International Conference on Embedded Software and Systems
• 作者: Bashir, Qaisar;Pivezhandi, Mohammad;Saifullah, Abusayeed
• 通讯作者: Saifullah, Abusayeed

Transparent and Tamper-Proof Event Ordering in the Internet of Things Platforms

物联网平台中透明且防篡改的事件排序

• DOI: 10.1109/jiot.2022.3222450
• 发表时间: 2023-03
• 期刊: IEEE Internet of Things Journal
• 影响因子: 10.6
• 作者: Rahman, Mahbubur;Saifullah, Abusayeed
• 通讯作者: Saifullah, Abusayeed

Boosting Reliability and Energy-Efficiency in Indoor LoRa

提高室内 LoRa 的可靠性和能效

• DOI: 10.1145/3576842.3582327
• 发表时间: 2023-05-09
• 期刊: Proceedings of the 8th ACM/IEEE Conference on Internet of Things Design and Implementation
• 作者: Mahbubur Rahman;Abusayeed Saifullah
• 通讯作者: Abusayeed Saifullah