Due to the great help on the efficiency of industrial applications, Industrial IoT (IIoT) has been experiencing rapid development. 5G coupled with network slicing and multi-access edge computing technologies, is a promising networking solution for IIoT applications and offers many advantages for IIoT operators, such as customized service accommodation, local computation and a unified communication protocol. However, it essentially faces many challenges in network management and interworking.
The required flexibility and efficiency of network management and interworking would not be well addressed by relying on static and manual configurations. Instead, the system has to be constantly self-adjusted according to different types of devices and different requirements of applications, and be able to deal with dynamic and changing demands from IIoT applications. Artificial intelligence (AI) and machine learning (ML) techniques have been showing their merits on advanced network management and interworking, playing a central role in the orchestration of IIoT applications. However, many challenges still need to be tackled for the efficient and flexible management and interworking of IIoT networks. There are strong needs to design AI-based management schemes, to improve flexibility and efficiency, while still satisfying the stringent requirements of IIoT applications, e.g., guaranteed QoS, especially, during the transition period of IIoT networks.
Given the strong interest in both industry and academia in the future development of network management and interworking for IIoT, this special issue is devoted to the most recent developments and research outcomes addressing the related theoretical and practical aspects on network management and interworking for IIoT. It also aims to provide worldwide researchers and practitioners an ideal platform to innovate new solutions targeting at the corresponding key challenges.
Topics of interest for this special issue, include, but are not limited to the following:
Network slicing architectures and deployment practices for IIoT applications
5G slicing and slice management for IIoT
Virtualization and management of 5G mobile edge computing for IIoT
Interworking of different IIoT protocols during transition to full 5G/6G networks
Meeting QoS requirement of different IIoT protocols after translating into 5G protocol
AI-empowered management and interworking among heterogeneous IIoT protocols
AI-empowered orchestration and control of 5G slicing for IIoT
Self-driving networks and autonomous networks for IIoT
Experience and deployment of industrial application-network integration
Virtualization of resources, services and functions in SDN and NFV towards flexible Industrial IoT
Security and privacy for AI-enabled IIoT management and interworking
Submitted papers should present original, unpublished work, relevant to one of the topics of the Special Issue. All submitted papers will be evaluated on the basis of relevance, significance of contribution, technical quality, and quality of presentation. Manuscripts need to prepared according to Guide for Authors at https://www.journals.elsevier.com/computer-networks. We invite the prospective authors to submit their manuscript, via the online submission system in the main journal page and select “IIoT Management” as the Article Type. Please make sure you mention in your cover letter that you are submitting to this special issue.
Manuscript Submission Deadline: December 1st, 2020
Initial Decision: March 1st, 2021
Revised Manuscript Due: April 1st, 2021
Final Decision: May 15th, 2021
Final Manuscript Due: June 1st, 2021
Publication of Completed Special Issue: Q4 2021
Dr. Yulei Wu, University of Exeter, UK (Co-Lead)
Professor Laizhong Cui, Shenzhen University, China (Co-Lead)
Professor Victor C. M. Leung, The University of British Columbia, Canada
Professor Tarik Taleb, Aalto University, Finland
Professor Sangheon Pack, Korea University, Korea