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AuthorBaccour, Emna
AuthorAllahham, Mhd Saria
AuthorErbad, Aiman
AuthorMohamed, Amr
AuthorHussein, Ahmed Refaey
AuthorHamdi, Mounir
Available date2023-05-21T08:37:24Z
Publication Date2023-02-01
Publication NameIEEE Communications Magazine
Identifierhttp://dx.doi.org/10.1109/MCOM.001.2200508
CitationBaccour, E., Allahham, M. S., Erbad, A., Mohamed, A., Hussein, A. R., & Hamdi, M. (2023). Zero Touch Realization of Pervasive Artificial Intelligence as a Service in 6G Networks. IEEE Communications Magazine, 61(2), 110-116.
ISSN0163-6804
URIhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85149001160&origin=inward
URIhttp://hdl.handle.net/10576/43117
AbstractThe vision of the upcoming 6G technologies, characterized by ultra-dense networks, low latency, and fast data rate, is to support pervasive artificial intelligence (PAI) using zero touch solutions enabling self-X (e.g., self-configuration, self-monitoring, and self-healing) services. However, the research on 6G is still in its infancy, and only the first steps have been taken to conceptualize its design, investigate its implementation, and plan for use cases. Toward this end, academia and industry communities have gradually shifted from theoretical studies of AI distribution to real-world deployment and standardization. Still, designing an end-to-end framework that systematizes the AI distribution by allowing easier access to the service using a third-party application assisted by zero touch service provisioning has not been well explored. In this context, we introduce a novel platform architecture to deploy a zero touch PAI as a service (PAlaaS) in 6G networks supported by a blockchain-based smart system. This platform aims to standardize the PAI at all levels of the architecture and unify the interfaces in order to facilitate service deployment across application and infrastructure domains, relieve users' worries about cost, security, and resource allocation, and at the same time respect the 6G's stringent performance requirements. As a proof of concept, we present a federated-learning-as-a-service use case where we evaluate the ability of our proposed system to self-optimize and self-adapt to the dynamics of 6G networks in addition to minimizing the users' perceived costs.
SponsorThis publication was made possible by NPRP13S-0205-200265 from the Qatar National Research Fund.
Languageen
PublisherIEEE
SubjectDense network
Network architecture
Queueing networks
TitleZero Touch Realization of Pervasive Artificial Intelligence as a Service in 6G Networks
TypeArticle
Pagination110-116
Issue Number2
Volume Number61
dc.accessType Abstract Only


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