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.

中文翻译：

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工业物联网智能网络切片管理综述：智能交通、智能能源和智能工厂的综合方法


网络切片已被广泛认为是一种有前途的技术，可以适应工业物联网 (IIoT) 的多种服务。智能交通、智能能源和智能工厂/制造是构成工业物联网骨干的三大关键服务。面对多样化需求的工业物联网业务，网络切片管理至关重要。对智能网络切片管理进行全面的研究对于为该领域的未来研究提供指导具有重要意义。在本文中，我们对网络切片管理的一般用例以及具体的工业物联网服务（包括智能交通、智能能源和智能工厂）进行了彻底的调查和分析，并强调了许多现有工作/调查的优点和缺点，以及当前的调查遵循一组重要标准。此外，我们还提出了一种针对 IIoT 的智能网络切片管理架构，重点关注上述三种 IIoT 服务。对于每项服务，我们提供了应用程序需求和网络切片架构以及相关支持技术的详细分析。进一步，我们从编排架构、AI辅助管理和运营、边缘计算赋能网络切片、可靠性和安全性等方面，对各个业务的网络切片编排和管理进行了深入的理解。对于所提出的智能网络切片管理架构及其在每个工业物联网服务中的应用，我们确定了可以指导未来研究的相应关键挑战和未决问题。 为了便于理解实施，我们提供了综合智慧交通、智慧能源、智慧工厂的智能网络切片管理案例。一些经验教训包括： 1）对于智能交通，有必要明确识别特定应用的服务功能链（SFC），并编排底层 VNF/PNF 以支持此类 SFC； 2）对于智慧能源来说，同时保证超低时延和极高的可靠性至关重要； 3）对于智能工厂来说，跨异构网络域的资源管理至关重要。我们希望这项调查对研究人员和工程师在工业物联网智能网络切片管理的创新和部署方面有所帮助。