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

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
JournalIEEE Communications Surveys & Tutorials
DOIs
Publication statusE-pub ahead of print - 10 Mar 2022

Bibliographical note

Funding Agency:
Hong Kong RGC Research Impact Fund (Grant Number: R5060-19)
LEO Dr David P. Chan Institute of Data Science
Shenzhen Science and Technology Innovation Commission (Grant Number: R2020A045)
10.13039/501100007040-Singapore University of Technology and Design (Grant Number: SUTD SRG-ISTD-2021-165)
10.13039/501100001809-National Natural Science Foundation of China (Grant Number: 61872310)
10.13039/501100000266-Engineering and Physical Sciences Research Council (Grant Number: EP/R030863/1)
General Research Fund (Grant Number: 152244/21E, 52203/20E and 52221/19E)

Publisher Copyright:
IEEE

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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