scholarly journals An Efficient Early Frame Breaking Strategy for RFID Tag Identification in Large-Scale Industrial Internet of Things

2021 ◽  
Vol 2021 ◽  
pp. 1-6
Author(s):  
Zhiyong He ◽  
Hanguang Luo
Keyword(s):  
Internet Of Things ◽  
Large Scale ◽  
The Other ◽  
Identification Performance ◽  
Industrial Internet Of Things ◽  
Tag Identification ◽  
Frame Size ◽  
Industrial Internet ◽  
Two Phases ◽  
Channel Environment

With the increase in the number of tags, an efficient approach of tag identification is becoming an urgent need in Industrial Internet of Things (IIoT). However, the identification performance of existing Aloha-based anticollision schemes is limited when the initial frame size is seriously mismatched with the actual tag population size. The performance will degrade further when IIoT is deployed in the error-prone channel environment. To optimize the identification performance of RFID system in an error-prone channel environment, we propose an efficient early frame breaking strategy based anticollision algorithm (EFB-ACA) with channel awareness. The EFB-ACA divides the whole tag identification process into two phases: convergence phase and identification phase. The function of convergence phase is to make the adjusted frame quickly converge to an appropriate size. The early frame breaking strategy is embedded in the convergence phase. Numerical results show that the proposed EFB-ACA algorithm outperforms the other methods on efficiency and stability in the error-prone channel. In addition, EFB-ACA algorithm also outperforms the other methods in the error-free channel.

scholarly journals Industrial Internet of Things Based Efficient and Reliable Data Dissemination Solution for Vehicular Ad Hoc Networks

2018 ◽  
Vol 2018 ◽  
pp. 1-16 ◽  
Author(s):  
Shahid Latif ◽  
Saeed Mahfooz ◽  
Naveed Ahmad ◽  
Bilal Jan ◽  
Haleem Farman ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Vehicular Ad Hoc Networks ◽  
Ad Hoc ◽  
Data Dissemination ◽  
The Other ◽  
Message Delivery ◽  
Industrial Internet Of Things ◽  
Traffic Conditions ◽  
Industrial Internet ◽  
Transmission Region

Industrial Internet of Things (IIoT) is the other name of industrial Internet. It integrates a variety of existing industrial automation technologies with computing, machine learning, and communication technologies. Vehicular ad hoc network, an application of IIoT, is a self-organized network of vehicles which tends to provide improved road safety, diminished traffic congestion, and ultimate comfort to the travellers. In VANETs, vehicles exchange data with each other directly or through roadside units (RSUs). Data dissemination in VANETs experiences numerous challenging issues including broadcast storm, network partitions, intermittent connectivity between vehicles, and limited bandwidth. In literature, various data dissemination schemes are proposed. However, most of these schemes are designed for either urban or highway VANET scenarios and evaluated under sparse or dense traffic conditions. Moreover, these schemes do not effectively overcome the aforementioned issues simultaneously. In this paper, we present a new data dissemination protocol for VANETs, which disseminates the emergency messages in different scenarios under varying traffic conditions. During dense traffic conditions, DDP4V employs the segmentation of transmission region of a vehicle in order to select the most appropriate next forwarding vehicle (NFV). Accordingly, it divides the transmission region of a vehicle in three distinct segments and selects vehicle(s) inside the highest priority segment to forward the message to all neighbour vehicles, whereas it also uses implicit acknowledgements for guaranteed message delivery during sparse traffic Conditions. Simulation results show that DDP4V protocol outperforms the other existing related protocols in terms of coverage, network overhead, collision, and end-to-end delay.

scholarly journals Attribute Reduction Based on Genetic Algorithm for the Coevolution of Meteorological Data in the Industrial Internet of Things

2019 ◽  
Vol 2019 ◽  
pp. 1-8 ◽  
Author(s):  
Yong Cheng ◽  
Zhongren Zheng ◽  
Jun Wang ◽  
Ling Yang ◽  
Shaohua Wan
Keyword(s):  
Genetic Algorithm ◽  
Internet Of Things ◽  
Meteorological Data ◽  
Attribute Reduction ◽  
Evolutionary Process ◽  
Population Diversity ◽  
The Other ◽  
Industrial Internet Of Things ◽  
Reduction Operation ◽  
Industrial Internet

Due to the problem of attribute redundancy in meteorological data from the Industrial Internet of Things (IIoT) and the slow efficiency of existing attribute reduction algorithms, attribute reduction based on a genetic algorithm for the coevolution of meteorological data was proposed. The evolutionary population was divided into two subpopulations: one subpopulation used elite individuals to assist crossover operations to increase the convergence speed of the algorithm, and the other subpopulation balanced the population diversity in the evolutionary process by introducing a random population; these two subpopulations completed the evolutionary operations together. With the TSDPSO-AR algorithm and ARAGA algorithm, the attribute reduction operation for precipitation in meteorological data was performed. The results showed that the proposed algorithm maintained the diversity of the population during evolution, improved the reduction performance, and simplified the information system.

scholarly journals A Collocation Method for Numerical Solution of Nonlinear Delay Integro-Differential Equations for Wireless Sensor Network and Internet of Things

Sensors ◽  
2020 ◽  
Vol 20 (7) ◽  
pp. 1962 ◽  
Author(s):  
Rohul Amin ◽  
Shah Nazir ◽  
Iván García-Magariño
Keyword(s):  
Wireless Sensor Network ◽  
Internet Of Things ◽  
Differential Equations ◽  
Sensor Network ◽  
Large Scale ◽  
Approximate Solutions ◽  
Wireless Sensor ◽  
Industrial Internet Of Things ◽  
Industrial Internet ◽  
Nonlinear Delay

Wireless sensor network and industrial internet of things have been a growing area of research which is exploited in various fields such as smart home, smart industries, smart transportation, and so on. There is a need of a mechanism which can easily tackle the problems of nonlinear delay integro-differential equations for large-scale applications of Internet of Things. In this paper, Haar wavelet collocation technique is developed for the solution of nonlinear delay integro-differential equations for wireless sensor network and industrial Internet of Things. The method is applied to nonlinear delay Volterra, delay Fredholm and delay Volterra–Fredholm integro-differential equations which are based on the use of Haar wavelets. Some examples are given to show the computational efficiency of the proposed technique. The approximate solutions are compared with the exact solution. The maximum absolute and mean square roots errors for distant number of collocation points are also calculated. The results show that Haar method is efficient for solving these equations for industrial Internet of Things. The results are compared with existing methods from the literature. The results exhibit that the method is simple, precise and efficient.

scholarly journals Analysis of Security Issues and Countermeasures for the Industrial Internet of Things

2021 ◽  
Vol 11 (20) ◽  
pp. 9393
Author(s):  
Shantanu Pal ◽  
Zahra Jadidi
Keyword(s):  
Internet Of Things ◽  
Large Scale ◽  
Security Analysis ◽  
Cyber Attacks ◽  
Security Requirements ◽  
Future Research ◽  
The Internet ◽  
Industrial Internet Of Things ◽  
Security Issues ◽  
Industrial Internet

Industrial Internet of Things (IIoT) can be seen as an extension of the Internet of Things (IoT) services and applications to industry with the inclusion of Industry 4.0 that provides automation, reliability, and control in production and manufacturing. IIoT has tremendous potential to accelerate industry automation in many areas, including transportation, manufacturing, automobile, marketing, to name a few places. When the benefits of IIoT are visible, the development of large-scale IIoT systems faces various security challenges resulting in many large-scale cyber-attacks, including fraudulent transactions or damage to critical infrastructure. Moreover, a large number of connected devices over the Internet and resource limitations of the devices (e.g., battery, memory, and processing capability) further pose challenges to the system. The IIoT inherits the insecurities of the traditional communication and networking technologies; however, the IIoT requires further effort to customize the available security solutions with more focus on critical industrial control systems. Several proposals discuss the issue of security, privacy, and trust in IIoT systems, but comprehensive literature considering the several aspects (e.g., users, devices, applications, cascading services, or the emergence of resources) of an IIoT system is missing in the present state of the art IIoT research. In other words, the need for considering a vision for securing an IIoT system with broader security analysis and its potential countermeasures is missing in recent times. To address this issue, in this paper, we provide a comparative analysis of the available security issues present in an IIoT system. We identify a list of security issues comprising logical, technological, and architectural points of view and consider the different IIoT security requirements. We also discuss the available IIoT architectures to examine these security concerns in a systematic way. We show how the functioning of different layers of an IIoT architecture is affected by various security issues and report a list of potential countermeasures against them. This study also presents a list of future research directions towards the development of a large-scale, secure, and trustworthy IIoT system. The study helps understand the various security issues by indicating various threats and attacks present in an IIoT system.

scholarly journals Research on RFID Anticollision Algorithms in Industrial Internet of Things

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Haizhong Qian
Keyword(s):  
Internet Of Things ◽  
Research Trends ◽  
Future Research ◽  
Identification Performance ◽  
Enabling Technology ◽  
Industrial Internet Of Things ◽  
Collision Problem ◽  
Industrial Internet ◽  
The Internet Of Things ◽  
Standard Framework

As a perception enabling technology of the Internet of Things, RFID can quickly identify target objects. The tag-to-tag collision problem seriously affects the identification performance of the RFID system, which causes the reader to be unable to accurately identify any tag within the specific time. The mainstream anticollision algorithms are limited by the performance bottleneck under the standard framework. In this paper, we analyze the features and merits of three kinds of algorithms in detail and propose a new algorithm architecture for RFID anticollision. Through the extensive experimental results comparison, we prove that the new architecture is effective to improve the performance of DFSA algorithms. Finally, we summarize the future research trends in the RFID anticollision algorithms.

scholarly journals Effective Dynamic Control Strategy of a Key Supplier with Multiple Downstream Manufacturers Using Industrial Internet of Things and Cloud System

Processes ◽  
2019 ◽  
Vol 7 (3) ◽  
pp. 172 ◽  
Author(s):  
Hyunsoo Lee
Keyword(s):  
Internet Of Things ◽  
Real Time ◽  
Large Scale ◽  
Dynamic Control ◽  
Joint Production ◽  
Cloud System ◽  
Industrial Internet Of Things ◽  
Real Time Control ◽  
Quality Issue ◽  
Industrial Internet

Intelligent data analytics-based cloud computing is a leading trend for managing a large-scale network in contemporary manufacturing environments. The data and information are shared using the cloud environments and valuable knowledge is driven using the embedded intelligence analytics. This research applied this trend to the control of a key supplier’s real-time production planning for solving joint production goals with downstream producers. As a key supplier has several downstream producers in general, several uncertainties are embedded on the supply chain network such as the quality issue in the supplier and the occurrence of unexpected orders from the downstream industries. While the control of a supply plan is difficult considering these dynamics in traditional frameworks, the proposed framework detects the dynamic changes accurately using the constructed cloud system. Moreover, the real-time control considering uncertain scenarios as well as the extracted knowledge is achieved using the provided Industrial Internet of Things (IIoT) and simulation-based control model using stochastic network. To show the effective of the suggested framework, real manufacturing cases and their numerical analyses are provided.

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