scholarly journals Software-Defined Networking Solutions, Architecture and Controllers for the Industrial Internet of Things: A Review

Sensors ◽  
2021 ◽  
Vol 21 (19) ◽  
pp. 6585
Author(s):  
Claudio Urrea ◽  
David Benítez
Keyword(s):  
Internet Of Things ◽  
Software Defined Networking ◽  
Network Control ◽  
Distributed Network ◽  
Industrial Internet Of Things ◽  
Analytic Hierarchy ◽  
Core Element ◽  
Industrial Networks ◽  
Centralized Management ◽  
Industrial Internet

The use of Software-Defined Networking (SDN) in the communications of the Industrial Internet of Things (IIoT) demands more comprehensive solutions than those developed to date. The lack of an SDN solution applicable in diverse IIoT scenarios is the problem addressed in this article. The main cause of this problem is the lack of integration of a set of aspects that should be considered in a comprehensive SDN solution. To contribute to the solution of this problem, a review of the literature is conducted in this article, identifying the main requirements for industrial networks nowadays as well as their solutions through SDN. This review indicates that aspects such as security, independence of the network technology used, and network centralized management can be tackled using SDN. All the advantages of this technology can be obtained through the implementation of the same solution, considering a set of aspects proposed by the authors for the implementation of SDNs in IIoT networks. Additionally, after analyzing the main features and advantages of several architectures proposed in the literature, an architecture with distributed network control is proposed for all SDN network scenarios in IIoT. This architecture can be adapted through the inclusion of other necessary elements in specific scenarios. The distributed network control feature is relevant here, as it prevents a single fault-point for an entire industrial network, in exchange for adding some complexity to the network. Finally, the first ideas for the selection of an SDN controller suitable for IIoT scenarios are included, as this is the core element in the proposed architecture. The initial proposal includes the identification of six controllers, which correspond to different types of control planes, and ten characteristics are defined for selecting the most suitable controller through the Analytic Hierarchy Process (AHP) method. The analysis and proposal of different fundamental aspects for the implementation of SDNs in IIoT in this article contribute to the development of a comprehensive solution that is not focused on the characteristics of a specific scenario and would, therefore, be applicable in limited situations.

scholarly journals Development of the blockchain architecture of the Industrial Internet of Things system of the enterprise

2021 ◽  
Vol 16 (95) ◽  
pp. 16-32
Author(s):  
Emil A. Gumerov ◽  
◽  
Tamara V. Alekseeva ◽  
Keyword(s):  
Internet Of Things ◽  
Intelligent Systems ◽  
Software Agents ◽  
Modern World ◽  
Distributed Network ◽  
Industrial Internet Of Things ◽  
Industrial Internet ◽  
Security Problem ◽  
Cryptographic System ◽  
Financial Losses

The development of the digital economy in the modern world requires solving the issue of security of Industrial Internet of Things (IIoT) applications. A large number of distributed, network-based, IIoT devices managed by intelligent programs (software agents) require protection. A successful attack on any IIoT device will lead to hacking of the IIoT application and to large financial losses, as well as to the termination of the IIoT application, therefore, the research topic is relevant. The purpose of this article is to radically solve the security problem of the IIoT application by developing a blockchain architecture of the application. The authors were tasked with investigating all aspects of the blockchain system that ensure the security of IIoT application devices. The peculiarity of the blockchain system is that its participants are software agents that control the application devices. As a result of the research, the concept of the blockchain architecture of the IIoT application is proposed. He mechanisms of consensus of intelligent programs of IIoT devices as equal active participants of the blockchain network are investigated. The consensus mechanism and the cryptographic system of the distributed registry of the blockchain network increase the information security of the IIoT application. The synergistic effect of the blockchain system and intelligent systems of software agents of IIoT application devices significantly increases the efficiency of the solution. Intelligent systems of software agents and IIoT applications are effectively trained on the blockchain platform, and as a result, we get a decentralized supercomputer in the form of a blockchain system.

A multi-factor integration-based semi-supervised learning for address resolution protocol attack detection in SDIIoT

2021 ◽  
Vol 17 (12) ◽  
pp. 155014772110599
Author(s):  
Zhong Li ◽  
Huimin Zhuang
Keyword(s):  
Internet Of Things ◽  
Supervised Learning ◽  
Software Defined Networking ◽  
Training Data ◽  
Detection Methods ◽  
Industrial Internet Of Things ◽  
Data Set ◽  
Correct Judgment ◽  
Industrial Internet ◽  
Address Resolution Protocol

Nowadays, in the industrial Internet of things, address resolution protocol attacks are still rampant. Recently, the idea of applying the software-defined networking paradigm to industrial Internet of things is proposed by many scholars since this paradigm has the advantages of flexible deployment of intelligent algorithms and global coordination capabilities. These advantages prompt us to propose a multi-factor integration-based semi-supervised learning address resolution protocol detection method deployed in software-defined networking, called MIS, to specially solve the problems of limited labeled training data and incomplete features extraction in the traditional address resolution protocol detection methods. In MIS method, we design a multi-factor integration-based feature extraction method and propose a semi-supervised learning framework with differential priority sampling. MIS considers the address resolution protocol attack features from different aspects to help the model make correct judgment. Meanwhile, the differential priority sampling enables the base learner in self-training to learn efficiently from the unlabeled samples with differences. We conduct experiments based on a real data set collected from a deepwater port and a simulated data set. The experiments show that MIS can achieve good performance in detecting address resolution protocol attacks with F1-measure, accuracy, and area under the curve of 97.28%, 99.41%, and 98.36% on average. Meanwhile, compared with fully supervised learning and other popular address resolution protocol detection methods, MIS also shows the best performance.

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 A Survey of 802.15.4 TSCH Schedulers for a Standardized Industrial Internet of Things

Sensors ◽  
2021 ◽  
Vol 22 (1) ◽  
pp. 15
Author(s):  
Andreas Ramstad Urke ◽  
Øivind Kure ◽  
Knut Øvsthus
Keyword(s):  
Internet Of Things ◽  
Industrial Revolution ◽  
Future Research ◽  
Traffic Patterns ◽  
Industrial Internet Of Things ◽  
Historical Trends ◽  
Holistic View ◽  
Industrial Networks ◽  
Industrial Internet ◽  
Channel Hopping

Concepts such as Industry 4.0 and Cyber-Physical Systems may bring forward a new industrial revolution. These concepts require extensive connectivity far beyond what is provided by traditional industrial networks. The Industrial Internet of Things (IIoT) bridges this gap by employing wireless connectivity and IP networking. In order for wireless networks to meet the strict requirements of the industrial domain, the Time Slotted Channel Hopping (TSCH) MAC is often employed. The properties of a TSCH network are defined by the schedule, which dictates transmission opportunities for all nodes. We survey the literature for these schedulers, describe and organize them according to their operation: Centralized, Collaborative, Autonomous, Hybrid, and Static. For each category and the field as a whole, we provide a holistic view and describe historical trends, highlight key developments, and identify trends, such as the attention towards autonomous mechanisms. Each of the 76 schedulers is analyzed into their common components to allow for comparison between schedulers and a deeper understanding of functionality and key properties. This reveals trends such as increasing complexity and the utilization of centralized principles in several collaborative schedulers. Further, each scheduler is evaluated qualitatively to identify its objectives. Altogether this allows us to point out challenges in existing work and identify areas for future research, including fault tolerance, scalability, non-convergecast traffic patterns, and hybrid scheduling strategies.

scholarly journals Threats in Cyber Safety - Outline of the Problem

2020 ◽  
Vol 2 (1) ◽  
pp. 349-356
Author(s):  
Wojciech Gliń ◽  
Renata Stasiak-Betlejewska
Keyword(s):  
Internet Of Things ◽  
Industry 4.0 ◽  
Cyber Attacks ◽  
Industrial Internet Of Things ◽  
Industrial Networks ◽  
Cyber Threats ◽  
Industrial Internet ◽  
Cyber Safety ◽  
The Web

AbstractCurrently, the industry is called as Industry 4.0, Internet of Things, Industrial Internet of Things, where devices, machines, information, organizations and people are connected to the network. Every day meet new solutions for Industry 4.o can be met, but in parallel with these solutions there are also threats in the field of security of industrial networks. Such threats have been called cyber-attacks or cyber threats. Cybersecurity is the global name of a field aimed at counteracting all types of threats on the web. Cybersecurity is to raise awareness, inform, control and introduce solutions to counteract cyber threats. Enterprises, organizations dealing with the promotion of Industry 4.0, IoT, IIoT, form the appropriate groups, departments, companies whose goal is to counteract all types of cyber-attacks. At present, the thesis can be formulated that cybersecurity of the broadly understood network is more important than the implementation of Industry 4.0. The publication will attempt to present the threats that cybersecurity enterprises must face and the ways and methods to counter them.

Sign in / Sign up

Export Citation Format

Share Document