A survey of intelligent network slicing management for industrial IoT: Integrated approaches for smart transportation, smart energy, and smart factory

Yulei WU, Hong-ning DAI, Haozhe WANG, Zehui XIONG, Song GUO

Research output: Journal PublicationsJournal Article (refereed)peer-review

186 Citations (Scopus)

Abstract

Network 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.
Original languageEnglish
Pages (from-to)1175-1211
Number of pages37
JournalIEEE Communications Surveys & Tutorials
Volume24
Issue number2
Early online date10 Mar 2022
DOIs
Publication statusPublished - Jun 2022

Bibliographical note

Publisher Copyright:
IEEE

Funding

This work was supported in part by the Engineering and Physical Sciences Research Council (EPSRC) under Grant EP/R030863/1; in part by the Singapore University of Technology and Design under Grant SRG-ISTD-2021-165; in part by the Hong Kong RGC Research Impact Fund (RIF) under Project R5060-19; in part by the General Research Fund (GRF) under Project 152221/19E, Project 152203/20E, and Project 152244/21E; in part by the National Natural Science Foundation of China under Grant 61872310; in part by the Shenzhen Science and Technology Innovation Commission under Grant R2020A045; and in part by the LEO Dr. David P. Chan Institute of Data Science, Lingnan University.

Keywords

  • Network slicing
  • Autonomous vehicle
  • Smart energy
  • Smart factory
  • Orchestration and management
  • Intelligent networks
  • Computer architecture
  • Ultra reliable low latency communication
  • Orchestration and management.
  • Smart transportation
  • Industrial Internet of Things
  • Smart manufacturing

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