Industrial Networks Research Articles

A Review of the Information Technology and Operational Technology Convergence Using Internet of Things within the Circular Economy

Abstract The historical separation of Information Technology and Operational Technology in organizations, particularly in the industrial sector, is being challenged by the digital transformation. This shift towards a converged platform is driven by technological advancements, market pressures, and environmental and regulatory considerations. This paper explores the convergence of Information Technology and Operational Technology through the Internet of Things within the Circular Economy. A comprehensive overview of the current scientific literature is provided using a systematic review method. Initially, the evolving landscape of the Information Technology and Operational Technology integration is reviewed, then Internet of Things and Circular Economy are presented. The findings of this study include the challenges of the converged solution implementation, such as the technical integration complexities, cybersecurity risks, organizational and cultural barriers, and workforce skills gap. Furthermore, the role of the Internet of Things is demonstrated using novel smart circular loops, products, and applications showcasing innovative ideas such as product-as-a-service models, digital circular practices, products with embedded sensors, energy harvesting, and modular and upgrade capabilities as well as novel digital factory use cases such as smart manufacturing and industrial symbiosis networks. The key findings also outline the best practices and recommendations for a successful implementation of this converged infrastructure, highlighting the importance of a strategic implementation and cross-domain collaboration to achieve operational efficiency and environmental sustainability. The insights provided in this paper are valuable for academics, practitioners, and policymakers aimed to understand and harness the digital technologies for advancing sustainable practices towards a smart circular economy.

QoS Provision for Industrial IoT Networking: Multiantenna NOMA Based on Partial CSIT

QoS Provision for Industrial IoT Networking: Multiantenna NOMA Based on Partial CSIT

Ownership frictions in a procurement market: Evidence from London buses

This paper investigates the efficiency impact of garage ownership frictions in the procurement of public bus transportation services in London. In this market, operators are less competitive for routes far from their garages, leading to local monopoly rents. Empty bus travel between garages and routes (dead miles) is found to account for about 13 percent of driving time in this market. Consequentially, sizeable effects of dead mile minutes on bids and procurement costs are estimated. Taking the urban context and the demand side as given, and treating this market as a typical network industry, counterfactual simulations evaluate the effect of unbundling the ownership of bus garages from the operation of the bus routes. Letting a central dispatcher allocate buses to garages would reduce total dead miles by 14 percent, with corresponding reductions of operating costs and of polluting exhaust emissions.

블록모델링을 활용한 한국자동차산업 공급네트워크 구조 분석

This study empirically analyzes the supply network of the Korean automotive industry through CONCOR, a structural equivalence analysis, and blockmodeling. Using equivalence analysis, it is possible to classify nodes based on occupying the same position in the network and identify the relationship pattern between them, even if it is not based on direct connections between nodes. The results of the study are as follows First, the supply network of the Korean automobile industry was divided into six blocks, and the six domestic automakers belonged to different blocks. Second, we found that blocks 4 and 5 were significantly larger than blocks 1 and 2 in terms of attributes such as sales and total assets. Finally, the relational characteristics between the blocks suggest that block 5 plays a pivotal role in the supply network of the Korean automobile industry. The theoretical significance of this study is that it is the first to apply the concept of structural equivalence to the field of SCM research, providing a new way to systematically understand the structure of large and complex supply networks. In addition, from a practical perspective, it can help managers to view and understand the entire supply network from a macro perspective.

Monitoring of Industrial Hydraulic Processes Through Mobile Devices Connected to a Profinet Industrial Network

Monitoring of Industrial Hydraulic Processes Through Mobile Devices Connected to a Profinet Industrial Network

Local and Remote Control and Monitoring Through SmartClient and WebServer of an Industrial Network of an S7-1200 and a LOGO! PLC Based on the Industrial Ethernet Protocol for Electro-Pneumatic Processes

Local and Remote Control and Monitoring Through SmartClient and WebServer of an Industrial Network of an S7-1200 and a LOGO! PLC Based on the Industrial Ethernet Protocol for Electro-Pneumatic Processes

СУЧАСНІ ТЕНДЕНЦІЇ РОЗВИТКУ СИСТЕМ КОМПЕНСАЦІЇ РЕАКТИВНОЇ ПОТУЖНОСТІ

This paper surveys current trends and developments in reactive power compensation systems, elucidating their significance in enhancing system capacity and flexibility. By analyzing the capacity factor enhancement enabled by reactive power compensation, the study underscores its role in optimizing electricity delivery, thus conserving energy resources and facilitating the integration of renewable energy sources. It explores the key models and concepts driving advancements in reactive power compensation within power grids. As modern electrical systems grow in complexity, ongoing research into improving compensation methods becomes imperative to ensure the reliability and efficiency of industrial power grids. Future endeavors will involve developing a model utilizing real-world enterprise data to investigate the effects of technological variations in filter parameters on the performance of complex reactive power compensation schemes, encompassing both filters and capacitor banks. Keywords: reactive power, compensation systems, filter-compensating circuit, industrial power grid, electric power. Context. The paper considers the current trends used in the field of reactive power compensation, and the main directions of development of modern methods of reactive power compensation. Objective. The purpose of the work is to overview of current trends in the development of reactive power compensation systems, as well as an overview of possible ways of their effective application in various industrial networks. Methods. The paper presents a key aspect of reactive power compensation is its ability to increase system capacity and flexibility. By improving the capacity factor, utilities can deliver electricity more efficiently, reducing the need for excess capacity and thus conserving energy resources. In addition, this process plays an important role in supporting the integration of renewable energy sources such as wind and solar power, which often introduce volatility into electricity generation schemes. Results. The paper presents the main models and concepts in the field of reactive power compensation in power grids. Conclusions. Given the growing complexity of modern electrical systems, it is important to continue research into improving methods and means of reactive power compensation to ensure the reliability and efficiency of industrial power grids. In further research, it is planned to develop a model using a real enterprise as an example and investigate the impact of technological deviations of filter parameters on the steady-state and transient performance of complex reactive power compensation schemes, including not only filters but also capacitor banks.

НОВІТНІ ПРОТОКОЛИ БЕЗДРОТОВИХ МЕРЕЖ: ПЕРЕВАГИ ТА НЕДОЛІКИ

The authors examines the issues of Wireless Networks, which are the foundation of modern communication, providing Internet connectivity for millions of devices worldwide. With the advancement of technology, new protocols are emerging that promise improvements in speed, reliability, and security. This article will review the latest wireless network protocols, such as Wi-Fi 6 (802.11ax), Wi-Fi 6E, Wi-Fi 7 (802.11be), and 5G, as well as their advantages and disadvantages. The growing number of connected devices requires networking solutions that can easily scale without sacrificing performance. In a world where there are many different devices and systems, the latest protocols must ensure interoperability between different manufacturers and technologies. Therefore, the problems of the latest wireless network protocols are closely related to important scientific and practical tasks facing modern society. Studying the advantages and disadvantages of these protocols is critical to ensure the efficient functioning of wireless communications in the future. The influence of the implementation of the latest protocols on the practical use of wireless networks in various fields, including communications, medicine, and industry, will be evaluated. An analysis of the competitiveness of the latest protocols in comparison with previous versions of the protocols and other competing technologies was also carried out, and recommendations were formulated for organizations and enterprises regarding the selection and implementation of the latest wireless network protocols, taking into account their advantages and disadvantages. Given an example with Wi-Fi 6, I used the Scapy library to create and send frames. This example demonstrates how you can configure frames for data transmission using Wi-Fi 6 technology. Using RadioTap and Dot11 allows you to configure the necessary parameters for wireless transmission.

Alternating optimized RIS-assisted noma and nonlinear partial differential deep reinforced satellite communication

Satellite communication is crucial for 6 G industrial wireless networks due to its comprehensive communication services, but traditional methods face challenges such as high latency, limited bandwidth, high cost, and integration with terrestrial networks. This highlights the need for innovative communication methods to boost satellite communication efficiency, reliability, and coverage within the context of 6 G industrial applications, which is attempted to address by this research. RISs (Reconfigurable Intelligent Surfaces) are thin sheets with tiny antennas that are programmed to manipulate radio signals. The RIS has the potential to revolutionize industrial wireless communication by providing greater dynamic and goal-oriented control over radio signals. From there, the wireless environment is being transformed into a service. Besides, the NOMA (Non-Orthogonal Multiple Access) mechanism is a highly effective radio access method in advanced wireless communications that optimizes spectrum utilization and offers improved spectrum efficiency, lower latency, more reliability, and increased connectivity. The current industrial communication network faces limitations such as limited capacity, signal interference overload, complex and expensive infrastructure, and latency issues. The fusion of RIS and NOMA is seen as promising strategy to meet the stringent demands of next-generation networks for immense connectivity. It is particularly innovative for the demanding environment of smart factories by enabling efficient resource sharing, dynamic signal control, ultra-reliable, low-latency communication, cost-effective network, overcoming the signal interference and simplifying the network infrastructure. In this article, we propose a novel approach for device-to-device satellite communication in industrial networks. This approach leverages a RIS (Reconfigurable Intelligent Surface) -assisted cooperative network with NOMA (Non-Orthogonal Multiple Access) and NL-PDDRL (Nonlinear Partial Differential Deep Reinforced Learning) termed AONPDDR (Alternating Optimized and Nonlinear Partial Differential Deep Reinforced) communication. This article focuses on important aspects related to industrial communication networks such as power consumption, energy efficiency, data delivery rate, data loss rate, throughput, latency, coverage, false alarm rate, and bit error rate. The Alternating Optimization-based RIS configuration algorithm optimizes reflecting elements in RIS by maximizing channel vectors and providing a sophisticated upper bound on the highest number of reflective elements. Next, The NL-PDDRL algorithm is designed to function effectively despite environmental uncertainties and constraints. The results indicate that the proposed AONPDDR method outperforms previous benchmark methods in system-achievable aspects.

DSME-FOTA: Firmware over-the-air update framework for IEEE 802.15.4 DSME MAC to enable large-scale multi-hop industrial IoT networks

The Internet of Things (IoT) is rapidly expanding in applications ranging from smart homes and smart cities to various other domains, including agriculture, transportation, industrial automation, and environmental monitoring. Regardless of the application domain, firmware update over-the-air (FOTA) capability is critical for any IoT network, and its importance is particularly evident in the field of industrial IoT. This paper presents a comprehensive solution designed for large-scale industrial IoT networks, with a special focus on Deterministic Synchronous Multi-channel Extension (DSME)-based multi-hop networks, called DSME-FOTA. The paper provides a detailed FOTA protocol design, a numerical analysis, and proof-of-concept experiments. The analytical and experimental results show that the total firmware update time of DSME-FOTA exhibits a first-order dependence on both the number of hops and the firmware binary size.

Addressing security challenges in industry 4.0: AVA-MA approach for strengthening SDN-IoT network security

In the context of Industry 4.0, the convergence of the Internet of Things (IoT) and Software Defined Networking (SDN) represents a challenging yet pivotal avenue for bolstering network security. This amalgamation facilitates the establishment of an integrated SDN-IoT platform that adeptly confronts the security intricacies arising from the evolving landscape of interconnected devices and industrial networks. Through the strategic application of SDN, the network architecture undergoes dynamic segmentation, responsive to diverse parameters encompassing device attributes, application contexts, and security imperatives. This segmentation strategy effectively isolates IoT devices, constricting the potential attack surface and correspondingly diminishing the ramifications of security breaches. Therefore, this paper proposed a novel Adaptive Variational Autoencoder-based Modified Archery (AVA-MA) method to enhance the security of IoT devices. In this study, samples are collected and used from both the TON-IoT dataset and the SDN dataset to determine the effectiveness of the proposed AVA-MA method. The evaluation measures such as AUC, F1-score, recall, accuracy, and precision are used to evaluate the performance of the proposed AVA-MA method. The results depict the AVA-MA method attained an accuracy of 98.95 %, precision of 97.54 %, recall of 95.64 %, and F1-score of 98.86 % respectively.

Design and Performance Evaluation of a Hybrid Active Power Filter Controller

This paper introduces a novel hybrid filter topology that combines passive and active components to enhance harmonic filtering and resonance damping in electrical power systems. The design integrates a three-phase two-level voltage-source converter with a double-tuned passive filter in parallel, significantly reducing the power rating and operational costs while maintaining good harmonic filtering performance and reactive current compensation. Double-tuned passive filters, compared to single-tuned ones, offer improved harmonic attenuation at multiple frequencies, enhancing overall system efficiency. Moreover, when used with the proposed hybrid filter topology, the double-tuned version allows for even lower dimensions of the active part, thereby further reducing system cost. A state-feedback controller is designed to enhance the performance of the hybrid filter, proving particularly effective in environments with complex impedance conditions. This paper also examines the impact of variations in passive component parameters, demonstrating the design’s robustness against potential deviations expected over the operational lifespan. The results indicate that the hybrid filter effectively mitigates harmonics and maintains operational stability under various transient conditions, as confirmed by analytical and simulation studies on a real industrial network model. These findings underline the hybrid filter’s potential to significantly improve power quality in modern electrical networks.

The impact of project‐based interorganizational networks: Evidence from the Chinese movie industry

AbstractProject‐based interorganizational networks are temporary and dynamic, and significantly different from stable networks for mass production. However, empirical studies on project‐based interorganizational networks are scant. Drawing upon the network literature and distinguishing between production and distribution networks, we investigate how the centrality of a project in industry networks and tie strength of the project's member firms affect project performance in terms of product quality and sales. Using data of 821 Chinese movie projects during 2015–2018, we find empirical evidence that a project's centrality in the production network enhances product quality and that in the distribution network elevates product sales. Interestingly, weak ties in the production team contribute to product quality while strong ties in the distribution team improve product sales. This study advances the literature on project‐based industries and interorganizational networks. It highlights the distinction between production and distribution networks in project‐based industries and sheds light on the differential roles of a project's centrality and tie strength in both networks. These findings also offer novel insights to managers in project‐based industries.

A Survey on AI-Empowered Softwarized Industrial IoT Networks

The future generation of mobile networks envision Artificial Intelligence (AI) and the Internet of Things (IoT) as key enabling technologies that will foster the emergence of sophisticated use cases, with the industrial sector being one to benefit the most. This survey reviews related works in this field, with a particular focus on the specific role of network softwarization. Furthermore, the survey delves into their context and trends, categorizing works into several types and comparing them based on their contribution to the advancement of the state of the art. Since our analysis yields a lack of integrated practical implementations and a potential desynchronization with current standards, we finalize our study with a summary of challenges and future research ideas.

Paving the way towards safer and more efficient maritime industry with 5G and Beyond edge computing systems

The Maritime and Road Transport and Logistics (T&L) vertical industries account for 92.5% of the European total freight transport. Therefore, efficient T&L systems in busy port environments are critical for Europe’s global competitiveness. The emergence of 5G and Beyond, including Standalone (SA) with data rates up to 20 Gbps, latencies as low as 5 milliseconds (ms), and exceptional reliability (99.999%), offers a significant opportunity for innovation in the Maritime sector, in terms of smarter and safer operations. In this paper, we investigate the enhancements brought forth by Edge Network-aware Applications (EdgeApps) strategically positioned at the network edge, focusing on a practical maritime use case denominated as “Assisted Vessel Navigation”, all within the overarching framework of the edge-cloud/core continuum paradigm. We utilize the so-called edge network softwarization and intelligence that allows us to create EdgeApps, capable of running on 5G and Beyond-enabled edge and cloud infrastructure to increase the safety and efficiency of maritime operations. The EdgeApp framework simplifies the creation of complex 5G and Beyond vertical services and fosters collaboration between industry stakeholders, network experts, and EdgeApp developers. The contributions of this paper are threefold: i) this paper focuses on the significance of edge computing systems within the 5G ecosystem and their role in enhancing vertical industries such as transport and logistics (T&L), with a specific focus on maritime applications, ii) the core contribution of this paper lies in the design and implementation of EdgeApps tailored to vertical industries. We explore their deployment in a real-life maritime environment, and iii) we share valuable insights derived from our real-life experiments conducted in the Port of Antwerp-Bruges, analyzing network and service performance results based on the use case requirements. Therefore, we examine the deployment options of EdgeApps, comparing edge versus cloud environments to assess where they need to run in the edge-cloud continuum. The outcomes and lessons learned from this article hold important implications for vertical industries.

V4RIN: visual analysis of regional industry network with domain knowledge.

The regional industry network (RIN) is a type of financial network derived from industry networks that possess the capability to describe the connections between specific industries within a particular region. For most investors and financial analysts lacking extensive experience, the decision-support information provided by industry networks may be too vague. Conversely, RINs express more detailed and specific industry connections both within and outside the region. As RIN analysis is domain-specific and current financial network analysis tools are designed for generalized analytical tasks and cannot be directly applied to RINs, new visual analysis approaches are needed to enhance information exploration efficiency. In this study, we collaborated with domain experts and proposed V4RIN, an interactive visualization analysis system that integrates predefined domain knowledge and data processing methods to support users in uploading custom data. Through multiple views in the system panel, users can comprehensively explore the structure, geographical distribution, and spatiotemporal variations of the RIN. Two case studies were conducted and a set of expert interviews with five domain experts to validate the usability and reliability of our system.

Digital Economy: Legal and Economic Status on the Example of the EAEU

The article discusses the legal and economic aspects of the development of the digital economy, highlighting the main elements of the digital economy, which become fundamental in the presence of digital platforms and the digital environment. The active implementation of information and communication technologies creates the basis for digital platforms for the introduction of new technologies and information relations based on the use of artificial intelligence, global industrial Internet networks of things and services, and big data technology. The development of services for the provision of online services, the development of online stores in new forms, the improvement of information sites, online communities and other forms of digital transformation of the economy, make it possible to extract more and more financial income by processing and providing more information through the digitalization of goods and services produced. The experience of introducing the digital agenda in the EAEU, including in trade relations, was studied, directions for digital transformation in the formation and development of the digital economy of the EAEU, aimed at creating a common information environment, including in the Internet space, were noted and proposed.

A federated learning approach to network intrusion detection using residual networks in industrial IoT networks

This paper introduces a sophisticated approach to network security, with a primary emphasis on utilizing deep learning for intrusion detection. In real-world scenarios, the high dimensionality of training data poses challenges for simple deep learning models and can lead to vanishing gradient issues with complex neural networks. Additionally, uploading network traffic data to a central server for training raises privacy concerns. To tackle these issues, the paper introduces a Residual Network (ResNet)-based deep learning model trained using a federated learning approach. The ResNet effectively tackles the vanishing gradient problem, while federated learning enables multiple Internet Service Providers (ISPs) or clients to engage in joint training without sharing their data with third parties. This approach enhances accuracy through collaborative learning while maintaining privacy. Experimental results on the X-IIoTID dataset indicate that the proposed model outperforms conventional deep learning and machine learning methods in terms of accuracy and other metrics used for evaluation. Specifically, the proposed methodology achieved 99.43% accuracy in a centralized environment and 99.16% accuracy in a federated environment.

Comparative Analysis of Classification Methods and Suitable Datasets for Protocol Recognition in Operational Technologies

The interconnection of Operational Technology (OT) and Information Technology (IT) has created new opportunities for remote management, data storage in the cloud, real-time data transfer over long distances, or integration between different OT and IT networks. OT networks require increased attention due to the convergence of IT and OT, mainly due to the increased risk of cyber-attacks targeting these networks. This paper focuses on the analysis of different methods and data processing for protocol recognition and traffic classification in the context of OT specifics. Therefore, this paper summarizes the methods used to classify network traffic, analyzes the methods used to recognize and identify the protocol used in the industrial network, and describes machine learning methods to recognize industrial protocols. The output of this work is a comparative analysis of approaches specifically for protocol recognition and traffic classification in OT networks. In addition, publicly available datasets are compared in relation to their applicability for industrial protocol recognition. Research challenges are also identified, highlighting the lack of relevant datasets and defining directions for further research in the area of protocol recognition and classification in OT environments.

Industrial technology network security measurement in international trade under discrete hopfield neural network

As global economic integration continues to advance, international trade has become increasingly vital for the economic development and growth of nations. This research aims to assess the trends in industrial technology security within China’s international trade and provide practical guidance for policy-making, corporate strategies, and international cooperation. The significance of the rising trend in security within China’s international trade industry lies in its establishment of a robust foundation for the long-term development of China’s international trade, contributing to its cooperation and competitiveness with other countries. In addressing the limitations of traditional measurement methods and providing a more comprehensive and accurate assessment of industrial technology security, this research presents an approach based on a discrete Hopfield Neural Network (HNN) for evaluating industrial technology security in international trade. This method integrates multiple indicators, including technology gap rates, to construct the Superior Quality Engineering (SQE) comprehensive evaluation model. The research employs a combination model of “entropy-grey relational-Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS)-discrete HNN” to assess industrial technology security. This research evaluates international trade industry technology security using patent data from 2015 to 2022 as samples. The results indicate an overall upward trend in security in China’s international trade industry. Within this trend, the research observes a stepwise increase in scale components, leading to continuous improvement in security. In terms of quality components, although security develops relatively slowly overall, it exhibits a trend of initial gradual decline followed by rapid growth. Regarding efficiency components, there is overall slow growth with periodic fluctuations. This research outcome provides substantial support for the research of industrial technology in international trade. The proposed method can assist businesses in evaluating their technological security in international trade and offer robust support for international trade decision-making.