Architecture Of Industrial Internet Research Articles

Lightweight Transmission Behavior Audit Scheme for NDN Industrial Internet Identity Resolution and Transmission Based on Blockchain

The Named Data Network (NDN) enables efficient content dissemination through interest-based retrieval, name-based routing, and content caching. In the industrial Internet architecture based on NDN, device identity distribution, identification, resolution, and routing rely on identification resolution technology. However, this approach presents challenges such as cache poisoning, interest packet flood attacks, and black hole attacks. Existing security schemes primarily focused on routing forwarding and verification fail to address critical concerns, including routing environment credibility and data leakage, while exhibiting poor time and space efficiency. To address these challenges, this paper proposes a lightweight behavior auditing scheme using blockchain technology. The scheme utilizes an improved Bloom filter to compress behavioral information like interest and data packets during the identification transmission process. The compressed data are subsequently uploaded to a blockchain for auditing, achieving efficient space and time utilization while maintaining feasibility.

A TRUSTED COMPUTING RESOURCES OPTIMAL SCHEDULING ALGORITHM IN INDUSTRIAL INTERNET AND HEALTHCARE INTEGRATING DRL, BLOCKCHAIN AND END-EDGE-CLOUD

With the rapid development of the Internet of Things (IoT) and Internet technology, the product of the combination of the two, the Industrial Internet, has also received extensive attention and there are more and more research achievements related to the Industrial Internet. In the industrial Internet system, the communication network system composed of sensors, communication nodes, controllers and other intelligent devices can realize efficient and convenient data interaction between people and machines, providing an important infrastructure and technical support for industrial big data analysis and intelligent production. However, in the current industrial Internet system, industrial equipment users generally have the problem of low computing energy efficiency, and the collected industrial data has a high-security risk in the transmission, processing and other processes. At the same time, the size and scale of the industrial Internet equipment group is huge, and the lack of rational resource allocation leads to excessive waste of computing resources in the system, which is also a prominent problem of the current industrial Internet system. In response to the above questions, this paper, on the basis of reading a large number of documents, integrates the improved DRL algorithm, End-Edge-Cloud architecture and blockchain to form a new industrial Internet architecture. The architecture realizes computing offload through the three-tier structure of terminal layer, edge layer and cloud layer, and guarantees the security of industrial data through the decentralized feature of blockchain, ultimately achieving the goal of reducing energy consumption, computing overhead and trusted computing. In the architecture proposed in this paper, the dynamic unloading of industrial data and computing tasks is achieved through a three-tier architecture. The MDP is used to build an optimization problem model, and the improved DRL algorithm is used to iteratively solve the optimal computing resource scheduling strategy. The main research contents of this paper include (1) Using MDP to model optimization problems; (2) Propose an industrial Internet system architecture that integrates and improves DRL, “end edge cloud” and blockchain; (3) The MDP problem is solved iteratively based on deep reinforcement learning. The simulation results show that the proposed architecture has more advantages than the existing six architectures in terms of computing cost, equipment energy consumption and total working time.

Scalable Identifier System for Industrial Internet Based on Multi-Identifier Network Architecture

Industrial Internet identifiers have the characteristics of heterogeneity, off-site, and foreign ownership. Traditional identifier systems encountered many problems, such as IP address exhaustion or difficulty in addressing and routing, which cannot meet the demands of numerous heterogeneous and interoperable Industrial Internet objects. At the same time, they also face various security risks. In this article, we propose multi-identifier network for Industrial Internet of Things (MIN-IIoT), a universal identifier system named multi-identifier network architecture for Industrial Internet, which supports the coexistence of multiple identifiers, such as identity, content names, services, locations, and IP addresses. MIN-IIoT establishes a unified identifier system and puts forward a series of identifier management methods, including identifier registration, addressing, mutual translation, and route forwarding. In addition, all identifier information is stored in a hierarchical consortium blockchain to ensure that they are authentic and immutable. Identity authentication, Proof of Vote (PoV)-based consensus algorithm, and trusted computing technology effectively protect the security of MIN-IIoT. Meanwhile, MIN-IIoT is convenient for deployment in various complex Industrial field environments. The extensive experiments show that MIN-IIoT has better performance in identifier management of Industrial Internet than traditional methods.

Design and Research of Teaching and Training Platform Based on Industrial Internet and Intelligent Manufacturing

Industrial internet and intelligent manufacturing application training platform is a comprehensive teaching and training platform for industrial internet, which contains a complete industrial internet architecture, including: sensing equipment, actuator, wireless sensor network, wired sensor network, industrial master control organization, industrial Internet cloud platform, industrial big data analysis platform. The industrial internet application technology training platform uses emerging technologies such as industrial internet, embedded, big data, mobile application, artificial intelligence, intelligent manufacturing, and built-in industrial internet cloud platform to provide teaching, practical training and scientific research support for the upgrading and reform of relevant disciplines in vocational colleges. The industrial internet and intelligent manufacturing training platform provides hardware and software resources with three layers of architecture, including equipment layer, platform layer and application layer, providing supporting teaching and practical training resources for related teaching. Industrial internet application technology training platform can meet the needs of industrial Internet teaching and training courses, including: "Industrial Ethernet and Network Equipment", "Network Security Technology", "Industrial Internet of Things", "Industrial Automation Control", "Network System Software Design", "Machine Vision Technology", "Manufacturing Execution System (MES) Application Technology" and so on.

SMA: SRv6-Based Multidomain Integrated Architecture for Industrial Internet

With the increasing requirements of industrial production efficiency, the Industrial Internet has played a very important role in the fourth industrial revolution. However, the current Industrial Internet still has many drawbacks, especially in terms of network systems, such as low network expansion, inconvenient troubleshooting, and low data transmission efficiency. For this motivation, a novel SRv6-based multidomain integrated architecture (SMA) for the Industrial Internet has been proposed. Multilayer controllers are deployed in the SMA, and a software-defined network controller that generates the transmission path is replaced by SMA nodes, which realizes the high network scalability and efficient data transmission of the Industrial Internet. The faulty node in the SMA can be quickly and accurately identified through the periodic detection actively sent by the controller node in the domain and the passive feedback of the SMA nodes, and the generated SMA node trusted set (SNTS) can be used for forwarding path generation. A Bellman–Ford algorithm with a hop count constraint based on the total number of SNTS nodes is proposed, which effectively avoids long-path forwarding and improves network resource utilization. Through theoretical analysis, the safety and scalability of the SMA have been fully verified. The simulation results of the SMA on the experimental platform show that the SMA is superior to the existing Industrial Internet network structure in terms of troubleshooting efficiency of faulty nodes, network throughput, and data communication overhead. In the Industrial Internet, when the proportion of SMA nodes reaches 30%, the SMA controller can control nearly 80% of the traffic. In addition, the maximum link utilization rate will be greatly reduced, which means better adjustment of network load balance.

Heuristic Routing Algorithms for Time-Sensitive Networks in Smart Factories.

Over recent years, traditional manufacturing factories have been accelerating their transformation and upgrade toward smart factories, which are an important concept within Industry 4.0. As a key communication technology in the industrial internet architecture, time-sensitive networks (TSNs) can break through communication barriers between subsystems within smart factories and form a common network for various network flows. Traditional routing algorithms are not applicable for this novel type of network, as they cause unnecessary congestion and latency. Therefore, this study examined the classification of TSN flows in smart factories, converted the routing problem into two graphical problems, and proposed two heuristic optimization algorithms, namely GATTRP and AACO, to find the optimal solution. The experiments showed that the algorithms proposed in this paper could provide a more reasonable routing arrangement for various TSN flows with different time sensitivities. The algorithms could effectively reduce the overall delay by up to 74% and 41%, respectively, with promising operating performances.

SEGA: Secured Edge Gateway Microservices Architecture for IIoT-Based Machine Monitoring

In this article, we propose SEGA, a secured edge gateway microservices architecture for industrial Internet of things-based monitoring of machines in industries. SEGA allows the secured collection, transmission, and temporary storage of data within the edge network. A k-nearest neighbors-based analytics module hosted on the edge gateway processes time-sensitive machine monitoring data on the gateway itself and identifies machines’ operational status. The system predicts the machine state and displays the monitored parameters such as current consumed, power factor, power consumption, and vibrational state of machinery. SEGA also enables secured offloading of data and advanced analytical functions from the edge gateway to the cloud. SEGA's deployment results show negligible changes in the edge gateway's performance due to the inclusion of various security and encryption mechanisms. However, the resource-constrained edge sensor nodes show an increase in wireless packet transmission latencies between them and the gateway by approximately 84.12 ms.

Provably Secure Architecture for Industrial Internet of Things in Smart Grid Based on Blockchain Technology

Provably Secure Architecture for Industrial Internet of Things in Smart Grid Based on Blockchain Technology

Industrial internet architecture for collaborative manufacturing of aviation equipment

Industrial internet architecture for collaborative manufacturing of aviation equipment

A Study on Intelligent Manufacturing Industrial Internet for Injection Molding Industry Based on Digital Twin

As one of the basic manufacturing industries in China, injection molding industry is faced with the problems of low degree of informatization and intelligence, resulting in low production efficiency and high costs. It is urgent to integrate deeply with new generation of information technology to achieve transformation and upgrade. In this paper, an integrative industrial Internet architecture of “integration of intelligent equipment, intelligent production lines, intelligent workshops, intelligent factories, and intelligent formats” was described. The injection molding intelligent control system, the production management, control platform based on the MES system, and other key technologies were researched. Also, the smart factory architecture based on digital twin was established, and the implementation method of the smart factory digital twin system was elaborated. The feasibility and effectiveness of the method had been verified through the industrial application, which provided the technical supports for the injection molding industrial Internet system. Finally, the intelligent manufacturing industrial Internet cloud platform for injection molding industry was prospected.

Design and Application of Distributed Computing Environment Based on Data Drive

This paper proposes a distributed computing environment based on data-driven mechanism, which can be deployed on different levels of Industrial Internet, designs and implements an Industrial Internet architecture with high reusability and rapid deployment. This architecture has the consistency of the computing environment in the cloud and terminal control layer, which is beneficial to the realization of remote management and collaborative control of Industrial Internet. Data driven technology enables heterogeneous industrial equipment to achieve interconnection and interworking at a low cost. The multi-engine computing environment constructed by it is not only an effective method to solve the application design and development of complex systems, but also a key technology to realize edge computing and fog computing. This paper designed a corresponding test bed platform, test results show that the technology can not only provide connectivity of heterogeneous data source and efficient technical support, and to ensure that the distributed industrial equipment real-time and synchronization of data transmission, but also has the strong edge computing capabilities to cope with the constantly generated data stream, and reducing the pressure of the cloud server storage, computing.

A Checkpoint Enabled Scalable Blockchain Architecture for Industrial Internet of Things

Industry 4.0 represents the fourth industrial revolution that will leverage the industrial Internet of Things (IIoT) to introduce adaptive and autonomous systems that can self-heal and self-learn. IIoT aims to promote businesses and industries by realizing intelligent industrialization. However, the constantly surging data volumes that are generated by IIoT environments present security issues like data integrity and system scalability. Blockchain is a promising candidate to address these problems, which offers distributed system design principles. Though blockchain-based IIoT frameworks may have the potential to support the demands and services of next-generation industrial systems, their integration is still constrained by significant challenges in scalability and security. Therefore, blockchain in its original structure with traditional proof-of-work consensus is not suitable for IIoT. To address this, we propose a blockchain architecture that uses a dynamic proof-of-work consensus with a block checkpoint mechanism. The dynamic consensus functions with different mining difficulty levels allow the architecture to efficiently scale with increase in communication traffic of IIoT devices, whereas the checkpoint defines an alternative mechanism to generate the next block hash in the blockchain. To study the scalability and feasibility of the architecture, thorough performance and security analyses are presented, which attest that it can scale and offer enhanced security fidelity with a minimal increase in block mining time.

A Secure Fog-Based Architecture for Industrial Internet of Things and Industry 4.0

The advent of Industrial Internet of Things (IIoT) along with cloud computing has brought a huge paradigm shift in manufacturing industries resulting in yet another industrial revolution, Industry 4.0. Huge amounts of delay-sensitive data of diverse nature are being generated, which need to be locally processed and secured because of their sensitivity. However, the low-end Internet of Things devices are unable to handle huge computational overheads. In addition, the semi-trusted nature of cloud introduces several security concerns. To address these issues, this article proposes a secure fog-based IIoT architecture by suitably plugging a number of security features into it and by offloading some of the tasks judiciously to fog nodes. These features secure the system alongside reducing the trust and burden on the cloud and resource-constrained devices, respectively. We validate our proposed architecture through both theoretical overhead analysis and practical experimentation, including simulation study and testbed implementation.

A reliable next generation cyber security architecture for industrial internet of things environment

Architectural changes are happening in the modern industries due to the adaption and the deployment of ‘Internet of Things (IoT)’ for monitoring and controlling various devices remotely from the external world. The most predominant place where the IoT technology makes the most sense is the industrial automation processes in smart industries (Industry 4.0). In this paper, a reliable ‘Next Generation Cyber Security Architecture (NCSA)’ is presented for Industrial IoT (IIoT) environment that detects and thwarts cybersecurity threats and vulnerabilities. It helps to automate the processes of exchanging real-time critical information between devices without any human intervention. It proposes an analytical framework that can be used to protect entities and network traffics involved in the IIoT wireless communication. It incorporates an automated cyber-defense authentication mechanism that detects and prevents security attacks when a network session has been established. The defense mechanism accomplishes the required level of security protection in the network by generating an identity token which is cryptographically encrypted and verified by a virtual gateway system. The proposed NCSA improves security in the IIoT environment and reduces operational management cost.

The architecture and key technologies for an industrial Internet with synergy between the cloud and clients

The fourth industrial revolution has been unveiled with the rapid development of Internet of things (IoT), cloud computing, and big data. The industrial Internet, as a highly cooperative and intelligence-sharing global network that connects entities, human beings, and the environment in smart manufacturing, is the core of this revolution. However, most current research on the industrial Internet is restricted to IoT, cloud computing, or big data, respectively. The synergy between the cloud and clients is currently at a very primary stage of sensing, connection, and knowledge, lacking a cloud-client-integrative architecture and key technologies that could meet the evolving requirements of networked smart production, including more complex objects to be sensed, more diversification of entities to be connected, faster data processing, and more intelligent feedback control. This paper first surveys some important research directions with respect to this research field and summarizes the research status and challenges. On this basis, a novel cloud-client integrative industrial Internet architecture and solutions for related key technologies are proposed. Then, the proposed technologies are demonstrated for some specific applications in the field of intelligent manufacturing. Finally, the prospects for cloud-client-integrative industrial Internet research are discussed and concluded.

Temperature Monitoring for Electrical Substations Using Infrared Thermography: Architecture for Industrial Internet of Things

Large corporations require smart interconnected cyber-physical systems that can interact and cooperate to reach common goals. The design of complex monitoring and fault detection systems based on this approach, usually referred to as Industrial Internet of Things, creates interconnected physical systems that generate value by providing more efficient manufacturing opportunities. However, this approach also creates important challenges, as the large number of sensors and devices provokes difficulties for configuration, application deployment, and service generation. This paper presents solutions for this advanced automation model, proposing an architecture for temperature monitoring and fault detection in electrical substations using infrared thermography. In this paper, systematic methods to apply flexible configurations and deployments are presented, including robust procedures to measure and monitor the temperature of electrical components. Architectural abstractions are also identified for this particular scenario. The proposed methodology and architecture are validated in a real-life case study in a large industrial organization.