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Guest editorial: AI-enabled software-defined industrial networks: Architectures, algorithms, and applications

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dc.contributor.author Han, G
dc.contributor.author Abu-Mahfouz, Adnan MI
dc.contributor.author Rodrigues, JJPC
dc.contributor.author Wang, X
dc.date.accessioned 2022-12-02T07:56:32Z
dc.date.available 2022-12-02T07:56:32Z
dc.date.issued 2022-06
dc.identifier.citation Han, G., Abu-Mahfouz, A.M., Rodrigues, J. & Wang, X. 2022. Guest editorial: AI-enabled software-defined industrial networks: Architectures, algorithms, and applications. <i>IEEE Transactions on Industrial Informatics, 18(6).</i> http://hdl.handle.net/10204/12547 en_ZA
dc.identifier.issn 1551-3203
dc.identifier.uri DOI: 10.1109/TII.2022.3142146
dc.identifier.uri http://hdl.handle.net/10204/12547
dc.description.abstract The papers in this special section focus on artificial intelligence-enabled software defined industrial networks. With the development of intelligent manufacturing, new manufacturing modes such as personalized customization and networked collaboration have been widely developed. These new manufacturing modes require frequent data exchanges between manufacturing machines and industrial information systems through the networks, and dynamically change according to the variations of orders, business, and environments, which cannot be supported in traditional manufacturing modes that focus on local and fixed processes. The current industrial network architecture cannot meet the needs of the aforementioned upcoming manufacturing mode. For example, there are many industrial network protocols, forming a complex industrial heterogeneous network, which seriously affects the interconnections between the underlying devices and the upper layer application systems. In addition, the layering information technology (IT) networks and the operation technology (OT) networks in the factory have hindered the developments of the industrial networks and intelligent manufacturing. There is an urgent need to build a flat, efficient, and flexible industrial network to support the new manufacturing modes. en_US
dc.format Abstract en_US
dc.language.iso en en_US
dc.relation.uri https://ieeexplore.ieee.org/document/9717361/authors en_US
dc.relation.uri https://ieeexplore.ieee.org/document/9717361 en_US
dc.source IEEE Transactions on Industrial Informatics, 18(6) en_US
dc.subject Artificial intelligence-enabled software en_US
dc.subject Industrial informatics en_US
dc.subject Industrial networks en_US
dc.title Guest editorial: AI-enabled software-defined industrial networks: Architectures, algorithms, and applications en_US
dc.type Article en_US
dc.description.pages 4210 - 4214 en_US
dc.description.note © 2022 IEEE. Due to copyright restrictions, the attached PDF file only contains the abstract of the full text item. For access to the full text item, please consult the publisher's website: https://ieeexplore.ieee.org/document/9717361 en_US
dc.description.cluster Next Generation Enterprises & Institutions en_US
dc.description.impactarea EDT4IR Management en_US
dc.identifier.apacitation Han, G., Abu-Mahfouz, A. M., Rodrigues, J., & Wang, X. (2022). Guest editorial: AI-enabled software-defined industrial networks: Architectures, algorithms, and applications. <i>IEEE Transactions on Industrial Informatics, 18(6)</i>, http://hdl.handle.net/10204/12547 en_ZA
dc.identifier.chicagocitation Han, G, Adnan MI Abu-Mahfouz, JJPC Rodrigues, and X Wang "Guest editorial: AI-enabled software-defined industrial networks: Architectures, algorithms, and applications." <i>IEEE Transactions on Industrial Informatics, 18(6)</i> (2022) http://hdl.handle.net/10204/12547 en_ZA
dc.identifier.vancouvercitation Han G, Abu-Mahfouz AM, Rodrigues J, Wang X. Guest editorial: AI-enabled software-defined industrial networks: Architectures, algorithms, and applications. IEEE Transactions on Industrial Informatics, 18(6). 2022; http://hdl.handle.net/10204/12547. en_ZA
dc.identifier.ris TY - Article AU - Han, G AU - Abu-Mahfouz, Adnan MI AU - Rodrigues, JJPC AU - Wang, X AB - The papers in this special section focus on artificial intelligence-enabled software defined industrial networks. With the development of intelligent manufacturing, new manufacturing modes such as personalized customization and networked collaboration have been widely developed. These new manufacturing modes require frequent data exchanges between manufacturing machines and industrial information systems through the networks, and dynamically change according to the variations of orders, business, and environments, which cannot be supported in traditional manufacturing modes that focus on local and fixed processes. The current industrial network architecture cannot meet the needs of the aforementioned upcoming manufacturing mode. For example, there are many industrial network protocols, forming a complex industrial heterogeneous network, which seriously affects the interconnections between the underlying devices and the upper layer application systems. In addition, the layering information technology (IT) networks and the operation technology (OT) networks in the factory have hindered the developments of the industrial networks and intelligent manufacturing. There is an urgent need to build a flat, efficient, and flexible industrial network to support the new manufacturing modes. DA - 2022-06 DB - ResearchSpace DP - CSIR J1 - IEEE Transactions on Industrial Informatics, 18(6) KW - Artificial intelligence-enabled software KW - Industrial informatics KW - Industrial networks LK - https://researchspace.csir.co.za PY - 2022 SM - 1551-3203 T1 - Guest editorial: AI-enabled software-defined industrial networks: Architectures, algorithms, and applications TI - Guest editorial: AI-enabled software-defined industrial networks: Architectures, algorithms, and applications UR - http://hdl.handle.net/10204/12547 ER - en_ZA
dc.identifier.worklist 26130 en_US


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