University of Oulu

X. Wang, X. Ren, C. Qiu, Y. Cao, T. Taleb and V. C. M. Leung, "Net-in-AI: A Computing-Power Networking Framework with Adaptability, Flexibility, and Profitability for Ubiquitous AI," in IEEE Network, vol. 35, no. 1, pp. 280-288, January/February 2021, doi: 10.1109/MNET.011.2000319

Net-in-AI : a computing-power networking framework with adaptability, flexibility, and profitability for ubiquitous AI

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Author: Wang, Xiaofei1; Ren, Xiaoxu1; Qiu, Chao1;
Organizations: 1College of Intelligence and Computing, Tianjin University, Tianjin, China
2Department of Communications and Networking, School of Electrical Engineering, Aalto University, Finland
3Department of Computer and Information Security, Sejong University, Seoul, South Korea
4Center for Wireless Communications, The University of Oulu, Oulu, Finland
5College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China
6Department of Electrical and Computer Engineering, The University of British Columbia, Vancouver, Canada
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 11.9 MB)
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Language: English
Published: Institute of Electrical and Electronics Engineers, 2021
Publish Date: 2021-06-03


Along with the unprecedented development of artificial intelligence (AI), a considerable number of intelligent applications are universally recognized to significantly facilitate the evolution of anthropogenic activities. The abundant AI computing power is one of the main pillars to fuel the booming of ubiquitous AI applications. As the computing power proliferates to a multitude of network edges, even end devices, the networking function bridges the gap, on the one hand, among ends-edges-clouds, on the other hand, between the multiple AI computing power and the heterogeneous AI requirements. The emerging new opportunities have spawned the deep integration between computing and networking. However, the complete development of the integrated system is under-addressed, including adaptability, flexibility, and profitability. In this article, we propose a computing-power networking framework for ubiquitous AI by establishing Networking in AI computing-power pool, denoted as Net-in-AI. We design the framework to enable the adaptability for computing-power users, the flexibility for networking, and the profitability for computing-power providers. We then formulate a computing-networking resource allocation problem, with the joint perspective of these three aspects. Experimental results prove the superior performance of the proposed framework in comparison to the current popular schemes.

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Series: IEEE network
ISSN: 0890-8044
ISSN-E: 1558-156X
ISSN-L: 0890-8044
Volume: 35
Issue: 1
Pages: 280 - 288
Article number: 9293089
DOI: 10.1109/MNET.011.2000319
Type of Publication: A1 Journal article – refereed
Field of Science: 213 Electronic, automation and communications engineering, electronics
Funding: This work was supported in part by the National Key R & D Program of China through Grant No. 2019YFB2101901; the National NSFC through Grants No. 62072332 and 62002260; and the China Postdoctoral Science Foundation under Grant No. 2020M670654. This work was also partially supported by the European Union Horizon 2020 Research and Innovation Program through the MonB5G Project under Grant No. 871780; the Academy of Finland Project CSN under Grant Agreement 311654; and the 6Gene-sis project under Grant No. 318927.
Academy of Finland Grant Number: 318927
Detailed Information: 318927 (Academy of Finland Funding decision)
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