Show simple item record

dc.contributor.authorWu, Y
dc.contributor.authorDai, H-N
dc.contributor.authorWang, H
dc.contributor.authorXiong, Z
dc.contributor.authorGuo, S
dc.date.accessioned2022-03-21T11:38:26Z
dc.date.issued2022-03-10
dc.date.updated2022-03-21T09:40:47Z
dc.description.abstractNetwork slicing has been widely agreed as a promising technique to accommodate diverse services for the Industrial Internet of Things (IIoT). Smart transportation, smart energy, and smart factory/manufacturing are the three key services to form the backbone of IIoT. Network slicing management is of paramount importance in the face of IIoT services with diversified requirements. It is important to have a comprehensive survey on intelligent network slicing management to provide guidance for future research in this field. In this paper, we provide a thorough investigation and analysis of network slicing management in its general use cases as well as specific IIoT services including smart transportation, smart energy and smart factory, and highlight the advantages and drawbacks across many existing works/surveys and this current survey in terms of a set of important criteria. In addition, we present an architecture for intelligent network slicing management for IIoT focusing on the above three IIoT services. For each service, we provide a detailed analysis of the application requirements and network slicing architecture, as well as the associated enabling technologies. Further, we present a deep understanding of network slicing orchestration and management for each service, in terms of orchestration architecture, AI-assisted management and operation, edge computing empowered network slicing, reliability, and security. For the presented architecture for intelligent network slicing management and its application in each IIoT service, we identify the corresponding key challenges and open issues that can guide future research. To facilitate the understanding of the implementation, we provide a case study of the intelligent network slicing management for integrated smart transportation, smart energy, and smart factory. Some lessons learnt include: 1) For smart transportation, it is necessary to explicitly identify service function chains (SFCs) for specific applications along with the orchestration of underlying VNFs/PNFs for supporting such SFCs; 2) For smart energy, it is crucial to guarantee both ultra-low latency and extremely high reliability; 3) For smart factory, resource management across heterogeneous network domains is of paramount importance. We hope that this survey is useful for both researchers and engineers on the innovation and deployment of intelligent network slicing management for IIoT.en_GB
dc.description.sponsorshipEngineering and Physical Sciences Research Council (EPSRC)en_GB
dc.description.sponsorshipSingapore University of Technology and Design (SUTD)en_GB
dc.description.sponsorshipHong Kong RGC Research Impact Fund (RIF)en_GB
dc.description.sponsorshipNational Natural Science Foundation of Chinaen_GB
dc.description.sponsorshipShenzhen Science and Technology Innovation Commissionen_GB
dc.format.extent1-1
dc.identifier.citationPublished online 10 March 2022en_GB
dc.identifier.doihttps://doi.org/10.1109/comst.2022.3158270
dc.identifier.grantnumberEP/R030863/1en_GB
dc.identifier.grantnumberSRG-ISTD-2021-165en_GB
dc.identifier.grantnumberR5060-19en_GB
dc.identifier.grantnumber152221/19Een_GB
dc.identifier.grantnumber152203/20Een_GB
dc.identifier.grantnumber152244/21Een_GB
dc.identifier.grantnumber61872310en_GB
dc.identifier.grantnumberR2020A045en_GB
dc.identifier.urihttp://hdl.handle.net/10871/129106
dc.identifierORCID: 0000-0003-0801-8443 (Wu, Yulei)
dc.language.isoenen_GB
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en_GB
dc.rights© 2022 IEEEen_GB
dc.subjectNetwork slicingen_GB
dc.subjectAutonomous vehicleen_GB
dc.subjectSmart energyen_GB
dc.subjectSmart factoryen_GB
dc.subjectOrchestration and managementen_GB
dc.titleA Survey of Intelligent Network Slicing Management for Industrial IoT: Integrated Approaches for Smart Transportation, Smart Energy, and Smart Factoryen_GB
dc.typeArticleen_GB
dc.date.available2022-03-21T11:38:26Z
dc.identifier.issn1553-877X
dc.descriptionThis is the author accepted manuscript. The final version is available from IEEE via the DOI in this recorden_GB
dc.identifier.eissn1553-877X
dc.identifier.journalIEEE Communications Surveys and Tutorialsen_GB
dc.relation.ispartofIEEE Communications Surveys & Tutorials, PP(99)
dc.rights.urihttp://www.rioxx.net/licenses/all-rights-reserveden_GB
dcterms.dateAccepted2022
rioxxterms.versionAMen_GB
rioxxterms.licenseref.startdate2022-03-10
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2022-03-21T11:33:07Z
refterms.versionFCDAM
refterms.dateFOA2022-03-21T11:38:44Z
refterms.panelBen_GB


Files in this item

This item appears in the following Collection(s)

Show simple item record