scholarly journals QoS-Driven Adaptive Trust Service Coordination in the Industrial Internet of Things

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2449
Author(s):  
Jin Qi ◽  
Zian Wang ◽  
Bin Xu ◽  
Mengfei Wu ◽  
Zian Gao ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Search Space ◽  
Gray Wolf ◽  
Service Coordination ◽  
Trust Evaluation ◽  
Industrial Internet Of Things ◽  
Industrial Services ◽  
Coordination Model ◽  
Industrial Internet ◽  
Industrial Iot

The adaptive coordination of trust services can provide highly dependable and personalized solutions for industrial requirements in the service-oriented industrial internet of things (IIoT) architecture to achieve efficient utilization of service resources. Although great progress has been made, trust service coordination still faces challenging problems such as trustless industry service, poor coordination, and quality of service (QoS) personalized demand. In this paper, we propose a QoS-driven and adaptive trust service coordination method to implement Pareto-efficient allocation of limited industrial service resources in the background of the IIoT. First, we established a Pareto-effective and adaptive industrial IoT trust service coordination model and introduced a blockchain-based adaptive trust evaluation mechanism to achieve trust evaluation of industrial services. Then, taking advantage of a large and complex search space for solution efficiency, we introduced and compared multi-objective gray-wolf algorithms with the particle swarm optimization (PSO) and dragonfly algorithms. The experimental results showed that by judging and blacklisting malicious raters quickly and accurately, our model can efficiently realize self-adaptive, personalized, and intelligent trust service coordination under the given constraints, improving not only the response time, but also the success rate in coordination.

scholarly journals Special Issue on New Industry 4.0 Advances in Industrial IoT and Visual Computing for Manufacturing Processes

2019 ◽  
Vol 9 (20) ◽  
pp. 4323 ◽  
Author(s):  
López de Lacalle ◽  
Posada
Keyword(s):  
Internet Of Things ◽  
Industry 4.0 ◽  
Research Community ◽  
Manufacturing Processes ◽  
Special Issue ◽  
Industrial Internet Of Things ◽  
Visual Computing ◽  
Industrial Internet ◽  
Industrial Iot ◽  
New Industry

The new advances of IIOT (Industrial Internet of Things), together with the progress in visual computing technologies, are being addressed by the research community with interesting approaches and results in the Industry 4.0 domain[...]

scholarly journals Visibility of resources and assets in the shipyard through industrial internet of things

2021 ◽  
Vol 11 (2) ◽  
pp. 88-101
Author(s):  
Ibrahim Cil ◽  
Fahri Arisoy ◽  
Hilal Kilinc
Keyword(s):  
Internet Of Things ◽  
Transformation Process ◽  
Digital Transformation ◽  
Sensor Data ◽  
Cyber Physical System ◽  
Industrial Internet Of Things ◽  
Use Of Data ◽  
Industrial Internet ◽  
Industrial Iot ◽  
Other Information

Industrial Internet of Things is becoming one of the fundamental technologies with the potential to be widely used in shipyards as in other industries to increase information visibility. This article aims to analyze how to develop an industrial IoT-enabled system that provides visibility and tracking of assets at SEDEF Shipyard, which is in the digital transformation process. The research made use of data from previous studies and by using content analysis, the findings were discussed. Industrial IoT enables the collection and analysis of data for more informed decisions.  Based on the findings, sensor data in the shipyard are transmitted to the cloud via connected networks. These data are analysed and combined with other information and presented to the stakeholders. Industrial IoT enables this data flow and monitors processes remotely and gives the ability to quickly change plans as needed. Keywords: Shipyard, Industrial Internet of Things, Cyber-Physical System, Visibility, Assets tracking;        

scholarly journals Design of the Wireless Network Hierarchy System of Intelligent City Industrial Data Management Based on SDN Network Architecture

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Wenken Tan ◽  
Jianmin Hu
Keyword(s):  
Internet Of Things ◽  
Access Control ◽  
Data Management ◽  
Wireless Network ◽  
Smart City ◽  
Network Architecture ◽  
Industrial Internet Of Things ◽  
Industrial Internet ◽  
Industrial Iot ◽  
Intelligent City

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.

scholarly journals Reliability Evaluation Model Of Industrial Internet Of Things Systems

2020 ◽  
Vol 1 (1) ◽  
pp. 22-24
Author(s):  
Dong-Seong Kim
Keyword(s):  
Internet Of Things ◽  
Performance Indicator ◽  
Evaluation Model ◽  
Industrial Internet Of Things ◽  
Research Issues ◽  
Industrial Systems ◽  
Performance Accuracy ◽  
Industrial Internet ◽  
Industrial Iot ◽  
Robust Systems

The Industrial Internet of Things (IIoT) allows digitizing manufacturing processes and increasing the digital connectivity of smart factory and industrial systems. The reliability of a system is considered as a key performance indicator that defines how accurately and perfectly the system works. Ensuring reliability in industrial IoT exposes several challenges as well as promising opportunities for advancing technologies and systematic designs such as algorithms, architectures, and devices. It depends on several factors, for example, ensuring performance, accuracy, stability, and availability. This article provides a systematic model for evaluating the reliability of IIoT systems. This model enables elucidate several open research issues regarding designing the reliable and robust systems.

scholarly journals Research on Traffic Detection Method of Secure Transmission Industrial Internet of Things Based on Computer Vision

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Donghui Yang
Keyword(s):  
Computer Vision ◽  
Internet Of Things ◽  
Industrial Development ◽  
Detection System ◽  
Industrial Internet Of Things ◽  
Statistical Point ◽  
Industrial Internet ◽  
Industrial Iot ◽  
Traffic Detection ◽  
Secure Transmission

In recent years, the process of industrial modernization has intensified, traditional industrial control has been improved and rapidly developed, industrial automation and intelligent unmanned production lines have become a new development trend, and the Internet of Things has become the basic direction of industrial development. In order to improve the effect of safe transmission and industrial IoT traffic detection, this study uses a neural network to improve the industrial IoT traffic detection algorithm. In order to improve the visualization effect of monitoring, this study uses computer vision technology to construct a traffic detection system of secure transmission industrial Internet of Things and builds an intelligent detection model. Finally, this study combines experimental research to verify the performance of the system. From the statistical point of view, it can be seen that the system’s security detection and traffic detection effects are very good.

scholarly journals Energy-Efficient Industrial Internet of Things Software-Defined Network by Means of the Peano Fractal

Sensors ◽  
2020 ◽  
Vol 20 (10) ◽  
pp. 2855 ◽  
Author(s):  
Jesus Jaime Moreno Escobar ◽  
Oswaldo Morales Matamoros ◽  
Ixchel Lina Reyes ◽  
Ricardo Tejeida-Padilla ◽  
Liliana Chanona Hernández ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Energy Efficient ◽  
State Of The Art ◽  
Economic Benefits ◽  
Wireless Sensor ◽  
Industrial Internet Of Things ◽  
Industrial Internet ◽  
Industrial Iot ◽  
Share Data ◽  
Light Diffusion

The Industrial Internet of Things (IIoT) network generates great economic benefits in processes, system installation, maintenance, reliability, scalability, and interoperability. Wireless sensor networks (WSNs) allow the IIoT network to collect, process, and share data of different parameters among Industrial IoT sense Node (IISN). ESP8266 are IISNs connected to the Internet by means of a hub to share their information. In this article, a light-diffusion algorithm in WSN to connect all the IISNs is designed, based on the Peano fractal and swarm intelligence, i.e., without using a hub, simply sharing parameters with two adjacent IINSs, assuming that any IISN knows the parameters of the rest of these devices, even if they are not adjacent. We simulated the performance of our algorithm and compared it with other state-of-the-art protocols, finding that our proposal generates a longer lifetime of the IIoT network when few IISNs were connected. Thus, there is a saving-energy of approximately 5% but with 64 nodes there is a saving of more than 20%, because the IIoT network can grow in a 3 n way and the proposed topology does not impact in a linear way but log 3 , which balances energy consumption throughout the IIoT network.

Nexus among intellectual capital, interorganizational learning, industrial Internet of things technology and innovation performance: a resource-based perspective

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Shafique Ur Rehman ◽  
Khurram Ashfaq ◽  
Stefano Bresciani ◽  
Elisa Giacosa ◽  
Jens Mueller
Keyword(s):  
Internet Of Things ◽  
Intellectual Capital ◽  
Innovation Performance ◽  
Industrial Internet Of Things ◽  
Interorganizational Learning ◽  
Content Type ◽  
Technology And Innovation ◽  
Industrial Internet ◽  
Industrial Iot

PurposeThe authors observe the influence of intellectual capital (IC) on innovation performance with the mediating role of interorganizational learning (IOL) in the Pakistani automotive industry. Besides, industrial Internet of things (IoT) technology is used as moderating variables between IOL and innovation performance.Design/methodology/approachStructural equation modeling (SEM) presents scholars with extra flexibility and enhanced research conclusions. SEM is described as a statistical methodology and the best tool used for hypothesis testing. The authors used partial least squares SEM for testing hypotheses. The simple random sampling technique followed to collect data from respondents, and 492 questionnaires were used for analysis.FindingsThe outcomes reveal that IC enhances innovation performance and IOL. Moreover, IOL increases innovation performance. IOL significantly mediates between IC and innovation performance. Industrial IoT technology improves innovation performance. Finally, industrial IoT technology strengthens the positive association between IOL and innovation performance.Practical implicationsThis study concentrates on the issue of how managers use IOL and industrial IoT technology to take higher advantage of IC that increases innovation performance.Originality/valueThis is the initial study that builds a theoretical framework to integrate IC, IOL, industrial IoT technology and innovation performance. Although prior researchers observe the association between IC and innovation performance, less concentration was paid to understand the role of interorganizational leadership and industrial IoT technology in leveraging organizational IC.

scholarly journals A Robust Predicted Performance Analysis Approach for Data-Driven Product Development in the Industrial Internet of Things

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2871 ◽  
Author(s):  
Hao Zheng ◽  
Yixiong Feng ◽  
Yicong Gao ◽  
Jianrong Tan
Keyword(s):  
Performance Analysis ◽  
Internet Of Things ◽  
Product Development ◽  
Data Driven ◽  
Analysis Approach ◽  
Design Solution ◽  
Support Vector ◽  
Industrial Internet Of Things ◽  
Industrial Internet ◽  
Industrial Iot

Industrial Internet of Things (IoT) is a ubiquitous network integrating various sensing technologies and communication technologies to provide intelligent information processing and smart control abilities for the manufacturing enterprises. The aim of applying industrial IoT is to assist manufacturers manage and optimize the entire product manufacturing process to improve product quality and production efficiency. Data-driven product development is considered as one of the critical application scenarios of industrial IoT, which is used to acquire the satisfied and robust design solution according to customer demands. Performance analysis is an effective tool to identify whether the key performance have reached the requirements in data-driven product development. The existing performance analysis approaches mainly focus on the metamodel construction, however, the uncertainty and complexity in product development process are rarely considered. In response, this paper investigates a robust performance analysis approach in industrial IoT environment to help product developers forecast the performance parameters accurately. The service-oriented layered architecture of industrial IoT for product development is first described. Then a dimension reduction approach based on mutual information (MI) and outlier detection is proposed. A metamodel based on least squares support vector regression (LSSVR) is established to conduct performance prediction process. Furthermore, the predicted performance analysis method based on confidence interval estimation is developed to deal with the uncertainty to improve the robustness of the forecasting results. Finally, a case study is given to show the feasibility and effectiveness of the proposed approach.

scholarly journals Real-Time Sensor Networks and Systems for the Industrial IoT: What Next?

Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5023
Author(s):  
Christos Koulamas ◽  
Mihai T. Lazarescu
Keyword(s):  
Sensor Networks ◽  
Internet Of Things ◽  
Real Time ◽  
Industrial Revolution ◽  
Cyber Physical Systems ◽  
Industrial Internet Of Things ◽  
Physical Systems ◽  
Industrial Internet ◽  
Industrial Iot

The Industrial Internet of Things (Industrial IoT—IIoT) is the emerging core backbone construct for the various cyber-physical systems constituting one of the principal dimensions of the 4th Industrial Revolution [...]

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