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Publication Date


Manuscript Submission Deadline

Special Issue

Call for Papers

While 5G has gradually opened the curtain of internet of everything and brings vertical transform to change the society, 6G is believed to open a new era of `Internet of Intelligence' with connected people, connected things, and connected intelligence, solving human challenges in many aspects and helping perfect the world we all live in. To empower 6G networks with AI capabilities, large volumes of multi-modal data (e.g., user behavior records, audios, and videos) of physical surroundings will be continuously generated by the mobile and IoT devices which reside at the network edge. Driving by this trend, there is an urgent need to push the AI frontiers to the network edge so as to fully unleash the potential 6G networks. To meet this demand, edge computing, an emerging paradigm that pushes computing tasks and services from the network core to the network edge, has been widely recognized as an indispensable part for the upcoming 6G networks.

While recognizing the benefits of edge computing for endowing the AI capabilities of 6G networks, the great potential of edge computing empowered by AI for 6G networks cannot be ignored. Specifically, with ubiquitous IoT devices as well as densely deployed and geographically distributed edge nodes, 6G networks will run on-top of distributed infrastructures across the cloud-edge-device hierarchy. However, orchestrating such a large, complex, and distributed networks to host AI applications is by no means trivial. For this problem, traditionally network optimization methodologies rely on fixed mathematical models; however, it is difficult to accurately model rapidly changing 6G network environments and systems. AI method is expected to deal with this problem: when faced with complex and cumbersome network information, AI method can rely on its powerful learning and reasoning ability to extract valuable information from data and make adaptive decisions, achieving intelligent resource management for 6G networks accordingly.

However, research on the nexus between edge computing and AI for 6G networks is still in a very early stage, a venue dedicated for discussion, promotion, and dissemination of research on the nexus between edge computing and AI for 6G networks is highly desired by both the computing and AI communities. To bridge this gap, this special issue aims at gathering the recent advances and novel contributions from academic researchers and industry practitioners in the novel area of the nexus between edge computing and AI for 6G networks, in order to fully leverage the potential capabilities and opportunities brought by this new inter-discipline. The scopes of this SI include, but are not limited to the following:

  • 6G network architectures and protocols for edge AI applications
  • Intelligent network edge resource management for 6G networks
  • Edge computing system and AI model co-design for 6G networks
  • Cloud-edge-device converged computing for AI in 6G networks
  • Federated edge learning over 6G networks
  • Distributed AI model training and inference over 6G networks
  • Privacy-preserving methods for edge AI in 6G networks
  • Distributed edge data analytics for 6G networks
  • Other emerging edge AI techniques and applications for 6G networks

Submission Guidelines

Prospective authors are invited to submit their manuscripts electronically, adhering to the IEEE Transactions on Network Science and Engineering guidelines. Note that the page limit is the same as that of regular papers. Please submit your papers through the online system and be sure to select the special issue or special section name. Manuscripts should not be published or currently submitted for publication elsewhere. Please submit only full papers intended for review, not abstracts, to the ScholarOne portal. If requested, abstracts should be sent by e-mail directly to the Guest Editors.

Important Dates

Manuscript Submission: 1 December 2021 4 January 2022 (Extended Deadline)
First Review Round: 1 March 2022
Revision Papers Due: 15 April 2022
Acceptance Notification: 1 June 2022
Final Manuscript Due: 15 June 2022
Publication: 2022

Guest Editors

Prof. Zhi Zhou
Sun Yat-sen University, China

Prof. Dusit Niyato
Nanyang Technological University, Singapore

Prof. Zehui Xiong
Singapore University of Technology and Design, Singapore

Prof. Xiaoweng Gong
Auburn University, United States

Prof. Walid Saad
Virginia Tech, United States

Prof. Xiaoming Fu
University of Göttingen, Germany