Edge Intelligence Offloading is a computational paradigm that involves the strategic delegation of artificial intelligence inference or training tasks from edge devices to proximal computing resources, distinguished by its optimization of resource utilization, latency reduction, and preservation of context-awareness within edge networks.
24
Publications
1.9K
Citations
104
Authors
45
Institutions
Publications per year
2017–2026
24
Parents
Publications
24
Edge Intelligence: Empowering Intelligence to the Edge of Network
Dianlei Xu, Tong Li, Yong Li et al. · Proceedings of the IEEE · 2021 · 247 citations · Full text
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Authors
104
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1–5 of 104
Institutions
45
Beijing University of Posts and Telecommunications
Beijing, China
4 h-index
13 publications
1K citations
Carleton University
Ottawa, Canada
4 h-index
7 publications
194 citations
Sun Yat-sen University
Guangzhou, China
3 h-index
7 publications
786 citations
Huazhong University of Science and Technology
Wuhan, China
3 h-index
5 publications
1.1K citations
Xidian University
Xi'an, China
3 h-index
5 publications
972 citations
Beijing Jiaotong University
Beijing, China
2 h-index
6 publications
136 citations
University of Electronic Science and Technology of China
Chengdu, China
2 h-index
8 publications
204 citations
Tsinghua University
Beijing, China
2 h-index
4 publications
857 citations
1–8 of 45
Venues
- IEEE Internet of Things Journal
6 publications · 338 citations
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- IEEE Network
3 publications · 73 citations
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- IEEE Transactions on Wireless Communications
2 publications · 240 citations
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- IEEE Vehicular Technology Magazine
1 publications · 39 citations
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- Future Internet
1 publications · 144 citations
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