scholarly journals Software Architecture of a Fog Computing Node for Industrial Internet of Things

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3715
Author(s):  
Ioan Ungurean ◽  
Nicoleta Cristina Gaitan
Keyword(s):  
Internet Of Things ◽  
Real Time ◽  
Development Process ◽  
Fog Computing ◽  
Low Latency ◽  
Practical Implementation ◽  
Industrial Internet Of Things ◽  
Industrial Internet ◽  
Starting Point ◽  
Hard Real Time

In the design and development process of fog computing solutions for the Industrial Internet of Things (IIoT), we need to take into consideration the characteristics of the industrial environment that must be met. These include low latency, predictability, response time, and operating with hard real-time compiling. A starting point may be the reference fog architecture released by the OpenFog Consortium (now part of the Industrial Internet Consortium), but it has a high abstraction level and does not define how to integrate the fieldbuses and devices into the fog system. Therefore, the biggest challenges in the design and implementation of fog solutions for IIoT is the diversity of fieldbuses and devices used in the industrial field and ensuring compliance with all constraints in terms of real-time compiling, low latency, and predictability. Thus, this paper proposes a solution for a fog node that addresses these issues and integrates industrial fieldbuses. For practical implementation, there are specialized systems on chips (SoCs) that provides support for real-time communication with the fieldbuses through specialized coprocessors and peripherals. In this paper, we describe the implementation of the fog node on a system based on Xilinx Zynq UltraScale+ MPSoC ZU3EG A484 SoC.

scholarly journals Toward Reliable Fog Computing Architecture for Industrial Internet of Things

2019 ◽  
Author(s):  
Muhammad Rusyadi Ramli ◽  
Sanjay Bhardwaj ◽  
Dong-Seong Kim
Keyword(s):  
Internet Of Things ◽  
Real Time ◽  
Fog Computing ◽  
Model Analysis ◽  
Industrial Internet Of Things ◽  
Reliable System ◽  
Computing Architecture ◽  
Industrial Networks ◽  
Industrial Internet

Reliability is essential in industrial networks. In addition, most of the data from nodes of industrial Internet of Things (IIoT) are generated in real time. Thus, those data are mainly used for the time-sensitive applications. Furthermore, device failures should be considered when modeling reliable fog computing for IIoT. In this paper, we provide fundamental aspects to model reliable fog computing for IIoT. First, existing models of fog computing are compared. Then, the most feasible communication type to achieve a reliable system is determined from model analysis. Interaction modes are elaborated to study the advantages and drawbacks when communication is deployed in fog computing for IIoT, and challenges and solutions for reliable fog computing are discussed.

scholarly journals Fog Computing Enabling Industrial Internet of Things: State-of-the-Art and Research Challenges

Sensors ◽  
2019 ◽  
Vol 19 (21) ◽  
pp. 4807 ◽  
Author(s):  
Rabeea Basir ◽  
Saad Qaisar ◽  
Mudassar Ali ◽  
Monther Aldwairi ◽  
Muhammad Ikram Ashraf ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Real Time ◽  
Data Exchange ◽  
Fog Computing ◽  
Building Blocks ◽  
Smart Devices ◽  
Industrial Internet Of Things ◽  
Computing Architecture ◽  
Research Challenges ◽  
Industrial Internet

Industry is going through a transformation phase, enabling automation and data exchange in manufacturing technologies and processes, and this transformation is called Industry 4.0. Industrial Internet-of-Things (IIoT) applications require real-time processing, near-by storage, ultra-low latency, reliability and high data rate, all of which can be satisfied by fog computing architecture. With smart devices expected to grow exponentially, the need for an optimized fog computing architecture and protocols is crucial. Therein, efficient, intelligent and decentralized solutions are required to ensure real-time connectivity, reliability and green communication. In this paper, we provide a comprehensive review of methods and techniques in fog computing. Our focus is on fog infrastructure and protocols in the context of IIoT applications. This article has two main research areas: In the first half, we discuss the history of industrial revolution, application areas of IIoT followed by key enabling technologies that act as building blocks for industrial transformation. In the second half, we focus on fog computing, providing solutions to critical challenges and as an enabler for IIoT application domains. Finally, open research challenges are discussed to enlighten fog computing aspects in different fields and technologies.

scholarly journals Adaptive Computing Optimization in Software-Defined Network-Based Industrial Internet of Things with Fog Computing

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2509 ◽  
Author(s):  
Juan Wang ◽  
Di Li
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Real Time ◽  
Fog Computing ◽  
Software Defined Network ◽  
Industrial Internet Of Things ◽  
Time Performance ◽  
Industrial Internet ◽  
Task Priority ◽  
Sdn Controller

In recent years, cloud computing and fog computing have appeared one after the other, as promising technologies for augmenting the computing capability of devices locally. By offloading computational tasks to fog servers or cloud servers, the time for task processing decreases greatly. Thus, to guarantee the Quality of Service (QoS) of smart manufacturing systems, fog servers are deployed at network edge to provide fog computing services. In this paper, we study the following problems in a mixed computing system: (1) which computing mode should be chosen for a task in local computing, fog computing or cloud computing? (2) In the fog computing mode, what is the execution sequence for the tasks cached in a task queue? Thus, to solve the problems above, we design a Software-Defined Network (SDN) framework in a smart factory based on an Industrial Internet of Things (IIoT) system. A method based on Computing Mode Selection (CMS) and execution sequences based on the task priority (ASTP) is proposed in this paper. First, a CMS module is designed in the SDN controller and then, after operating the CMS algorithm, each task obtains an optimal computing mode. Second, the task priorities can be calculated according to their real-time performance and calculated amount. According to the task priority, the SDN controller sends a flow table to the SDN switch to complete the task transmission. In other words, the higher the task priority is, the earlier the fog computing service is obtained. Finally, a series of experiments and simulations are performed to evaluate the performance of the proposed method. The results show that our method can achieve real-time performance and high reliability in IIoT.

scholarly journals Scalable Fog Computing Orchestration for Reliable Cloud Task Scheduling

2021 ◽  
Vol 11 (22) ◽  
pp. 10996
Author(s):  
Jongbeom Lim
Keyword(s):  
Internet Of Things ◽  
Task Scheduling ◽  
Industrial Revolution ◽  
Virtual Machines ◽  
Fog Computing ◽  
Industrial Internet Of Things ◽  
Industrial Internet ◽  
Virtualization Technology ◽  
Computing Environments ◽  
One Machine

As Internet of Things (IoT) and Industrial Internet of Things (IIoT) devices are becoming increasingly popular in the era of the Fourth Industrial Revolution, the orchestration and management of numerous fog devices encounter a scalability problem. In fog computing environments, to embrace various types of computation, cloud virtualization technology is widely used. With virtualization technology, IoT and IIoT tasks can be run on virtual machines or containers, which are able to migrate from one machine to another. However, efficient and scalable orchestration of migrations for mobile users and devices in fog computing environments is not an easy task. Naïve or unmanaged migrations may impinge on the reliability of cloud tasks. In this paper, we propose a scalable fog computing orchestration mechanism for reliable cloud task scheduling. The proposed scalable orchestration mechanism considers live migrations of virtual machines and containers for the edge servers to reduce both cloud task failures and suspended time when a device is disconnected due to mobility. The performance evaluation shows that our proposed fog computing orchestration is scalable while preserving the reliability of cloud tasks.

Improving the management of geographically distributed IB system using industrial technology Internet of things

2020 ◽  
pp. 143-149
Author(s):  
А.И. Сухотерин
Keyword(s):  
Internet Of Things ◽  
Real Time ◽  
Industrial Internet Of Things ◽  
Time Analysis ◽  
Real Time Analysis ◽  
Distributed Security ◽  
Industrial Internet ◽  
Is Management ◽  
Geographically Distributed ◽  
Key Indicators

В статье рассматривается проблемы управления ИБ на территориально-распределённых объектах защиты. Во избежание простоев и для сохранения безопасности на предприятии необходимо внедрение технологий, позволяющих обнаруживать и прогнозировать риски. Предлагается с помощью промышленного интернета-вещей обеспечить непрерывный интеллектуальный мониторинг ключевых показателей, что дает возможность определить проблему и принять необходимые меры для ее решения. Оперативный в режиме реального времени анализ поможет специалисту ИБ быстрее находить уязвимые места и предотвратить несанкционированные действия на предприятии. This article discusses the problems of is management on geographically distributed security objects. In order to avoid downtime and to maintain security at the enterprise, it is necessary to introduce technologies that allow detecting and predicting risks. It is proposed to use the industrial Internet of things to provide continuous intellectual monitoring of key indicators, which makes it possible to identify the problem and take the necessary measures to solve it. Real-time real-time analysis will help the IB specialist find vulnerabilities faster and prevent unauthorized actions in the enterprise .

Blockchain for Industrial Internet of Things (IIoT)

2021 ◽  
pp. 32-47
Author(s):  
Rinki Sharma
Keyword(s):  
Internet Of Things ◽  
Real Time ◽  
Manufacturing Process ◽  
Industrial Internet Of Things ◽  
Research Issues ◽  
Effective Implementation ◽  
Blockchain Technology ◽  
Industrial Internet ◽  
Manufacturing Applications ◽  
Decentralized Architecture

Over the years, the industrial and manufacturing applications have become highly connected and automated. The incorporation of interconnected smart sensors, actuators, instruments, and other devices helps in establishing higher reliability and efficiency in the industrial and manufacturing process. This has given rise to the industrial internet of things (IIoT). Since IIoT components are scattered all over the network, real-time authenticity of the IIoT activities becomes essential. Blockchain technology is being considered by the researchers as the decentralized architecture to securely process the IIoT transactions. However, there are challenges involved in effective implementation of blockchain in IIoT. This chapter presents the importance of blockchain in IIoT paradigm, its role in different IIoT applications, challenges involved, possible solutions to overcome the challenges and open research issues.

scholarly journals Industrial Internet of Things and Fog Computing to Reduce Energy Consumption in Drinking Water Facilities

Processes ◽  
2020 ◽  
Vol 8 (3) ◽  
pp. 282 ◽  
Author(s):  
Adrian Korodi ◽  
Ruben Crisan ◽  
Andrei Nicolae ◽  
Ioan Silea
Keyword(s):  
Drinking Water ◽  
Energy Consumption ◽  
Internet Of Things ◽  
Fog Computing ◽  
Industrial Internet Of Things ◽  
Non Invasive ◽  
Data Accumulation ◽  
Industrial Internet ◽  
Reduce Energy Consumption ◽  
And Control

The industry is generally preoccupied with the evolution towards Industry 4.0 principles and the associated advantages as cost reduction, respectively safety, availability, and productivity increase. So far, it is not completely clear how to reach these advantages and what their exact representation or impact is. It is necessary for industrial systems, even legacy ones, to assure interoperability in the context of chronologically dispersed and currently functional solutions, respectively; the Open Platform Communications Unified Architecture (OPC UA) protocol is an essential requirement. Then, following data accumulation, the resulting process-aware strategies have to present learning capabilities, pattern identification, and conclusions to increase efficiency or safety. Finally, model-based analysis and decision and control procedures applied in a non-invasive manner over functioning systems close the optimizing loop. Drinking water facilities, as generally the entire water sector, are confronted with several issues in their functioning, with a high variety of implemented technologies. The solution to these problems is expected to create a more extensive connection between the physical and the digital worlds. Following previous research focused on data accumulation and data dependency analysis, the current paper aims to provide the next step in obtaining a proactive historian application and proposes a non-invasive decision and control solution in the context of the Industrial Internet of Things, meant to reduce energy consumption in a water treatment and distribution process. The solution is conceived for the fog computing concept to be close to local automation, and it is automatically adaptable to changes in the process’s main characteristics caused by various factors. The developments were applied to a water facility model realized for this purpose and on a real system. The results prove the efficiency of the concept.

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