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How AI-enabled SDN technologies improve the security and functionality of industrial IoT network: Architectures, enabling technologies, and opportunities

Authors :
Jinfang Jiang
Chuan Lin
Guangjie Han
Adnan M. Abu-Mahfouz
Syed Bilal Hussain Shah
Miguel Martínez-García
Source :
Digital Communications and Networks, Vol 9, Iss 6, Pp 1351-1362 (2023)
Publication Year :
2023
Publisher :
KeAi Communications Co., Ltd., 2023.

Abstract

The ongoing expansion of the Industrial Internet of Things (IIoT) is enabling the possibility of effective Industry 4.0, where massive sensing devices in heterogeneous environments are connected through dedicated communication protocols. This brings forth new methods and models to fuse the information yielded by the various industrial plant elements and generates emerging security challenges that we have to face, providing ad-hoc functions for scheduling and guaranteeing the network operations. Recently, the large development of Software-Defined Networking (SDN) and Artificial Intelligence (AI) technologies have made feasible the design and control of scalable and secure IIoT networks. This paper studies how AI and SDN technologies combined can be leveraged towards improving the security and functionality of these IIoT networks. After surveying the state-of-the-art research efforts in the subject, the paper introduces a candidate architecture for AI-enabled Software-Defined IIoT Network (AI-SDIN) that divides the traditional industrial networks into three functional layers. And with this aim in mind, key technologies (Blockchain-based Data Sharing, Intelligent Wireless Data Sensing, Edge Intelligence, Time-Sensitive Networks, Integrating SDN&TSN, Distributed AI) and improve applications based on AI-SDIN are also discussed. Further, the paper also highlights new opportunities and potential research challenges in control and automation of IIoT networks.

Details

Language :
English
ISSN :
23528648
Volume :
9
Issue :
6
Database :
Directory of Open Access Journals
Journal :
Digital Communications and Networks
Publication Type :
Academic Journal
Accession number :
edsdoj.7174328cb2474d1a8577104b5691f40b
Document Type :
article
Full Text :
https://doi.org/10.1016/j.dcan.2022.07.001