Record link: 
http://hdl.handle.net/20.500.12708/195918
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Title: 
Distributed AI in Zero-touch Provisioning for Edge Networks: Challenges and Research Directions
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Citation: 
Hazra, A., Morichetta, A., Murturi, I., Loven, L., Dehury, C. K., Casamayor Pujol, V., Donta, P. K., & Dustdar, S. (2023). Distributed AI in Zero-touch Provisioning for Edge Networks: Challenges and Research Directions. arXiv. https://doi.org/10.48550/arXiv.2311.17471
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Publisher DOI: 
10.48550/arXiv.2311.17471
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Publication Type: 
Preprint
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Language: 
English
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Authors: 
Hazra, Abhishek 
Morichetta, Andrea 
Murturi, Ilir 
Loven, Lauri 
Dehury, Chinmaya Kumar 
Casamayor Pujol, Victor 
Donta, Praveen Kumar 
Dustdar, Schahram 
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Organisational Unit: 
E194-02 - Forschungsbereich Distributed Systems 
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ArXiv ID: 
arXiv:2311.17471
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Date (published): 
2023
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Number of Pages: 
7
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Preprint Server: 
arXiv 
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Keywords: 
Distributed Artificial Intelligence; Edge Networks; Edge Resource Federation; Internet of Things; Zero-touch Provisioning
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Abstract: 
Zero-touch network is anticipated to inaugurate the generation of intelligent and highly flexible resource provisioning strategies where multiple service providers collaboratively offer computation and storage resources. This transformation presents substantial challenges to network administration and service providers regarding sustainability and scalability. This article combines Distributed Artificial Intelligence (DAI) with Zero-touch Provisioning (ZTP) for edge networks. This combination helps to manage network devices seamlessly and intelligently by minimizing human intervention. In addition, several advantages are also highlighted that come with incorporating Distributed AI into ZTP in the context of edge networks. Further, we draw potential research directions to foster novel studies in this field and overcome the current limitations.
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Project (external): 
Academy of Finland through the 6G Flagship program
European Commission and select member countries through the ECSEL JU FRACTAL project
Business Finland through the Neural pub/sub research project
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Project ID: 
Grant 318927
Grant 877056
diary number 8754/31/2022
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Later published as: 
10.1109/MC.2023.3334913
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Research Areas: 
Information Systems Engineering: 100%
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Science Branch: 
1020 - Informatik: 100%
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Appears in Collections:
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