A Full-Wireless Network Architecture Based on the Industrial Internet of Things Paradigm

With the rapid development of the industrial Internet of Things and the comprehensive popularization of mobile intelligent devices, the construction of smart city and economic development of wireless network demand are increasingly high. SDN has the advantages of control separation, programmable interface, and centralized control logic. Therefore, integrating this technical concept into the smart city data management WLAN network not only can effectively solve the problems existing in the previous wireless network operation but also provide more functions according to different user needs. In this case, the traditional WLAN network is of low cost and is simple to operate, but it cannot guarantee network compatibility and performance. From a practical perspective, further network compatibility and security are a key part of industrial IoT applications. This paper designs the network architecture of smart city industrial IoT based on SDN, summarizes the access control requirements and research status of industrial IoT, and puts forward the access control requirements and objectives of industrial IoT based on SDN. The characteristics of the industrial Internet of Things are regularly associated with data resources. In the framework of SDN industrial Internet of Things, gateway protocol is simplified and topology discovery algorithm is designed. The access control policy is configured on the gateway. The access control rule can be dynamically adjusted in real time. An SDN-based intelligent city industrial Internet of Things access control function test platform was built, and the system was simulated. The proposed method is compared with other methods in terms of extension protocol and channel allocation algorithm. Experimental results verify the feasibility of the proposed scheme. Finally, on the basis of performance analysis, the practical significance of the design of a smart city wireless network hierarchical data management system based on SDN industrial Internet of Things architecture is expounded.

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Measurement and Characterization of Electromagnetic Noise in Edge Computing Networks for the Industrial Internet of Things

Sensors ◽

10.3390/s19143104 ◽

2019 ◽

Vol 19 (14) ◽

pp. 3104 ◽

Cited By ~ 1

Author(s):

Huiting Li ◽

Liu Liu ◽

Yiqian Li ◽

Ze Yuan ◽

Kun Zhang

Keyword(s):

Internet Of Things ◽

Wireless Network ◽

Markov Models ◽

Edge Computing ◽

Industrial Internet Of Things ◽

Statistical Parameters ◽

Electromagnetic Noise ◽

Technological Basis ◽

Industrial Internet ◽

Measurement Results

Edge computing and the Internet of Things (IOT) provide the technological basis for the development of intelligent manufacturing nowadays. In order to support the intelligent interconnection and application of all kinds of equipment in the industrial field, edge computing should be equipped close to or embedded in all kinds of equipment nodes in the industrial wireless network. Therefore, it is meaningful to investigate the wireless network design of the Industrial Internet of Things. Low power wireless sensor devices are widely used in the Industrial Internet of Things (IIoT), which are sensitive to electromagnetic noise. The electromagnetic noises in industrial scenarios are significantly different from the conventional assumed white noise. In this paper, the measurement results of electromagnetic noises at three different test positions are given in an automobile factory. The spectrum occupancy of the factory wireless environment in the 300 MHz–3 GHz band was obtained by frequency domain measurement. In the time domain measurement, four statistical parameters of the three bands of 315 MHz, 433 MHz, and 916 MHz were measured, and the electromagnetic noise distributions in different plant areas and different frequency bands were analyzed. According to the measurement results, the time-varying characteristics of electromagnetic noise can be characterized by continuous hidden Markov models (CHMM). These results are informative to the design and optimization for the edge computing networks for IIoT.

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A security‐driven network architecture for routing in industrial Internet of Things

Transactions on Emerging Telecommunications Technologies ◽

10.1002/ett.4216 ◽

2021 ◽

Author(s):

Jian Cao ◽

Xingwei Wang ◽

Min Huang ◽

Bo Yi ◽

Qiang He

Keyword(s):

Internet Of Things ◽

Network Architecture ◽

Industrial Internet Of Things ◽

Industrial Internet

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Pro-Edge: A Programmable Edge Network Architecture for Industrial Internet of Things

10.36227/techrxiv.16885003.v1 ◽

2021 ◽

Author(s):

Nurzaman Ahmed ◽

Mehbub Alam ◽

Rakesh Matam ◽

Ferdous Ahmed Barbhuiya ◽

Mithun Mukherjee

Keyword(s):

Internet Of Things ◽

Energy Efficient ◽

Network Architecture ◽

Middle Layer ◽

Industrial Applications ◽

Automation System ◽

Industrial Internet Of Things ◽

Edge Network ◽

Industrial Internet ◽

Sdn Controller

Internet of Things (IoT) with edge computation enhances efficiency, safety, and availability of an industrial automation system. However, there is a continued effort to increase the reliability of the system with minimal downtime. This can be achieved through a modular, re-configurable, and integrable system design approach. In this paper, we propose Pro-Edge, a programmable edge network to reconfigure different services associated with industrial applications and networks. Pro-Edge employs programmable layers at the edge for re-configuring the sensor/actuator network and applications. The lowermost layer allows to reconfigure the communication related parameters and the middle layer consists of a Software-Defined Network (SDN) controller that can dynamically program different modules, handling actuation decisions from the edge. An interfacing protocol between the layers is proposed to provide reliability by considering the optimal configuration parameters among the layers. As a top-layer, a priority forwarding mechanism is designed for SDN core communication in case the sensor and actuator are in different edges. Pro-Edge significantly improves the actuation-latency and is highly energy efficient compared to the existing state-of-the-art.

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Pro-Edge: A Programmable Edge Network Architecture for Industrial Internet of Things

10.36227/techrxiv.16885003 ◽

2021 ◽

Author(s):

Nurzaman Ahmed ◽

Mehbub Alam ◽

Rakesh Matam ◽

Ferdous Ahmed Barbhuiya ◽

Mithun Mukherjee

Keyword(s):

Internet Of Things ◽

Energy Efficient ◽

Network Architecture ◽

Middle Layer ◽

Industrial Applications ◽

Automation System ◽

Industrial Internet Of Things ◽

Edge Network ◽

Industrial Internet ◽

Sdn Controller

Internet of Things (IoT) with edge computation enhances efficiency, safety, and availability of an industrial automation system. However, there is a continued effort to increase the reliability of the system with minimal downtime. This can be achieved through a modular, re-configurable, and integrable system design approach. In this paper, we propose Pro-Edge, a programmable edge network to reconfigure different services associated with industrial applications and networks. Pro-Edge employs programmable layers at the edge for re-configuring the sensor/actuator network and applications. The lowermost layer allows to reconfigure the communication related parameters and the middle layer consists of a Software-Defined Network (SDN) controller that can dynamically program different modules, handling actuation decisions from the edge. An interfacing protocol between the layers is proposed to provide reliability by considering the optimal configuration parameters among the layers. As a top-layer, a priority forwarding mechanism is designed for SDN core communication in case the sensor and actuator are in different edges. Pro-Edge significantly improves the actuation-latency and is highly energy efficient compared to the existing state-of-the-art.

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An Integrated Legacy of Modbus Devices to Industrial Internet of Things: Approach for Smart Industries

10.31219/osf.io/54tje ◽

2020 ◽

Author(s):

Karthik Muthineni

Keyword(s):

Internet Of Things ◽

Industrial Revolution ◽

Digital Technologies ◽

Industrial Internet Of Things ◽

Intelligent Decision Making ◽

Internet Of Everything ◽

Industrial Internet ◽

Intelligent Decision ◽

Network Platform ◽

Smart Factories

The new industrial revolution Industry 4.0, connecting manufacturing process with digital technologies that can communicate, analyze, and use information for intelligent decision making includes Industrial Internet of Things (IIoT) to help manufactures and consumers for efficient controlling and monitoring. This work presents the design and implementation of an IIoT ecosystem for smart factories. The design is based on Siemens Simatic IoT2040, an intelligent industrial gateway that is connected to modbus sensors publishing data onto Network Platform for Internet of Everything (NETPIE). The design demonstrates the capabilities of Simatic IoT2040 by taking Python, Node-Red, and Mosca into account that works simultaneously on the device.

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MONITORING AND PREDICTIVE ANALYTICS OF TECHNOLOGICAL EQUIPMENT ON THE BASED OF INDUSTRIAL INTERNET OF THINGS

ВЕСТНИК ВОРОНЕЖСКОГО ГОСУДАРСТВЕННОГО ТЕХНИЧЕСКОГО УНИВЕРСИТЕТА ◽

10.36622/vstu.2020.16.5.001 ◽

2020 ◽

pp. 7-12

Author(s):

С.Л. Добрынин ◽

В.Л. Бурковский

Keyword(s):

Internet Of Things ◽

Data Acquisition ◽

Predictive Analytics ◽

Actual State ◽

Monitoring And Control ◽

Industrial Internet Of Things ◽

Machining Time ◽

Industrial Internet ◽

Acquisition Device ◽

Data Acquisition Device

Произведен обзор технологий в рамках концепции четвертой промышленной революции, рассмотрены примеры реализации новых моделей управления технологическими процессами на базе промышленного интернета вещей. Описано техническое устройство основных подсистем системы мониторинга и контроля, служащей для повышения осведомленности о фактическом состоянии производственных ресурсов в особенности станков и аддитивного оборудования в режиме реального времени. Архитектура предлагаемой системы состоит из устройства сбора данных (УСД), реализующего быстрый и эффективный сбор данных от станков и шлюза, передающего ликвидную часть информации в облачное хранилище для дальнейшей обработки и анализа. Передача данных выполняется на двух уровнях: локально в цехе, с использованием беспроводной сенсорной сети (WSN) на базе стека протоколов ZigBee от устройства сбора данных к шлюзам и от шлюзов в облако с использованием интернет-протоколов. Разработан алгоритм инициализации протоколов связи между устройством сбора данных и шлюзом, а также алгоритм выявления неисправностей в сети. Расчет фактического времени обработки станочных подсистем позволяет более эффективно планировать профилактическое обслуживание вместо того, чтобы выполнять задачи обслуживания в фиксированные интервалы без учета времени использования оборудования We carried out a review of technologies within the framework of the concept of the fourth industrial revolution; we considered examples of the implementation of new models of process control based on the industrial Internet of things. We described the technical structure of the main subsystems of the monitoring and control system to increase awareness of the actual state of production resources in particular machine tools and additive equipment in real time. The architecture of the proposed system consists of a data acquisition device (DAD) that implements fast and efficient data collection from machines and a gateway that transfers the liquid part of information to the cloud storage for further processing and analysis. We carried out the data transmission at two levels, locally in the workshop, using a wireless sensor network (WSN) based on ZigBee protocol stack from the data acquisition device to the gateways and from the gateways to the cloud using Internet protocols. An algorithm was developed for initializing communication protocols between a data acquisition device and a gateway, as well as an algorithm for detecting network malfunctions. Calculating the actual machining time of machine subsystems allows us to more efficiently scheduling preventive maintenance rather than performing maintenance tasks at fixed intervals without considering equipment usage

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