A Survey of Intelligent Network Slicing Management for Industrial IoT: Integrated Approaches for Smart Transportation, Smart Energy, and Smart Factory

被引:146
作者
Wu, Yulei [1 ]
Dai, Hong-Ning [2 ]
Wang, Haozhe [1 ]
Xiong, Zehui [3 ]
Guo, Song [4 ]
机构
[1] Univ Exeter, Coll Engn Math & Phys Sci, Exeter EX4 4QF, Devon, England
[2] Lingnan Univ, Dept Comp & Decis Sci, Hong Kong, Peoples R China
[3] Singapore Univ Technol & Design, Pillar Informat Syst Technol & Design, Singapore, Singapore
[4] Hong Kong Polytech Univ, Dept Comp, Hong Kong, Peoples R China
来源
IEEE COMMUNICATIONS SURVEYS AND TUTORIALS | 2022年 / 24卷 / 02期
基金
英国工程与自然科学研究理事会; 中国国家自然科学基金;
关键词
Industrial Internet of Things; Network slicing; Smart manufacturing; Smart transportation; Computer architecture; Intelligent networks; Ultra reliable low latency communication; autonomous vehicle; smart energy; smart factory; orchestration and management; LOW-LATENCY; ARTIFICIAL-INTELLIGENCE; FUNCTION VIRTUALIZATION; ORCHESTRATION PLATFORM; COMPREHENSIVE SURVEY; RESOURCE-MANAGEMENT; WIRELESS NETWORKS; CORE NETWORK; 5G; INTERNET;
D O I
10.1109/COMST.2022.3158270
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:1175 / 1211
页数:37
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