Revisiting Edge AI: Opportunities and Challenges

Author:

Meuser Tobias1ORCID,Lovén Lauri2ORCID,Bhuyan Monowar3ORCID,Patil Shishir G.4ORCID,Dustdar Schahram5ORCID,Aral Atakan3ORCID,Bayhan Suzan6ORCID,Becker Christian7ORCID,Lara Eyal de8ORCID,Ding Aaron Yi9ORCID,Edinger Janick10ORCID,Gross James11ORCID,Mohan Nitinder12ORCID,Pimentel Andy D.13ORCID,Rivière Etienne14ORCID,Schulzrinne Henning15ORCID,Simoens Pieter16ORCID,Solmaz Gürkan17ORCID,Welzl Michael18ORCID

Affiliation:

1. Technical University of Darmstadt, 64283, Darmstadt, Germany

2. University of Oulu, 90014 Oulu, Finland

3. Umeå University, 90187 Umeå, Sweden

4. UC Berkeley, California, Berkeley, CA, 94709, USA

5. Vienna University of Technology, Vienna 1040, Austria

6. University of Twente, 7500 AE, Enschede, The Netherlands

7. University of Stuttgart, 70569, Stuttgart, Germany

8. University of Toronto, Toronto, ON, M5S 1A1, Canada

9. TU Delft, 2600 AA, Delft, The Netherlands

10. University of Hamburg, 22527, Hamburg, Germany

11. Royal Institute of Technology Stockholm (KTH), 100 44 Stockholm, Sweden

12. Technical University of Munich, 80333, Munich, Germany

13. University of Amsterdam, 1098 GH, Amsterdam, The Netherlands

14. UCLouvain, B-1348, Louvain-la-Neuve, Belgium

15. Columbia University, New York, NY, 10027, USA

16. Ghent University-imec, B-9052, Gent, Belgium

17. NEC Laboratories Europe, 69115, Heidelberg, Germany

18. University of Oslo, 0313, Oslo, Norway

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Reference27 articles.

1. A survey of Deep Neural Network watermarking techniques

2. Roadmap for edge AI

3. Revisiting the Arguments for Edge Computing Research

4. Edge Computing: Vision and Challenges

5. EdgeAI: A vision for distributed, edge-native artificial intelligence in future 6G networks;Lovén,2019

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