Record link: 
http://hdl.handle.net/20.500.12708/198642
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Title: 
Task-Oriented 6G Native-AI Network Architecture
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Citation: 
Yang, Y., Wu, J., Chen, T., Peng, C., Wang, J., Deng, J., Tao, X., Liu, G., Li, W., Yang, L., He, Y., Yang, T., Aghvami, A. H., Eliassen, F., Dustdar, S., Niyato, D., Sun, W., Xu, Y., Yuan, Y., … Dai, C. (2024). Task-Oriented 6G Native-AI Network Architecture. IEEE Network, 38(1), 219–227. https://doi.org/10.1109/MNET.2023.3321464
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Publisher DOI: 
10.1109/MNET.2023.3321464
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Publication Type: 
Article - Original Research Article
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Language: 
English
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Authors: 
Yang, Yang 
Wu, Jianjun 
Chen, Tianjiao 
Peng, Chenghui 
Wang, Jun 
Deng, Juan 
Tao, Xiaofeng 
Liu, Guangyi 
Li, Wenjing 
Yang, Li 
He, Yufeng 
Yang, Tingting 
Aghvami, A. Hamid 
Eliassen, Frank 
Dustdar, Schahram 
Niyato, Dusit 
Sun, Wanfei 
Xu, Yang 
Yuan, Yannan 
Xie, Jiang 
Li, Rongpeng 
Dai, Cuiqin 
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Organisational Unit: 
E194-02 - Forschungsbereich Distributed Systems 
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Journal: 
IEEE Network 
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ISSN: 
0890-8044
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Date (published): 
Jan-2024
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Number of Pages: 
9
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Publisher: 
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
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Peer reviewed: 
Yes
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Keywords: 
6G; Native AI; Network Architecture; Artificial Intelligence
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Abstract: 
The vision for 6G networks is to offer pervasive intelligence and internet of intelligence, in which the networks natively support artificial intelligence (AI), empower smart applications and scenarios in various fields, and create a “ubiquitous-intelligence” world. In this vision, the traditional session-oriented architecture cannot achieve flexible per-user customization, ultimate performance, security and reliability required by future AI services.
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Project (external): 
National Key Research and Development Program of China
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Project ID: 
Grant 2020YFB2104300
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Research Areas: 
Information Systems Engineering: 100%
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Science Branch: 
1020 - Informatik: 100%
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