AI-Assisted Edge Computing for Multi-Tenant Management of Edge Devices in 6G Networks
Publication Date
1-1-2023
Document Type
Conference Proceeding
Publication Title
International Conference on 6G Networking, 6GNet 2023
DOI
10.1109/6GNet58894.2023.10317735
Abstract
Load management and the ability to dynamically change the virtual network topology in edge cloud computing exhibits a challenge when presented in 6G networks. This article presents how an assisted artificial intelligence (AI)-based approach substantially improves tasks of the edge and embedded edge cloud computing. This approach would meet the service requirements for virtual machine (VM) assignments and their communications scenarios. We show an analysis that indicates the time required to reconfigure a virtual network of a device tenant is successfully decreased when AI-assisted method is used. We compare the effectiveness of multi-tenancy structures of edge and embedded edge cloud networks both with and without AI option at the edge cloud segment of computing process.
Keywords
6G Networks, artificial intelligence (AI), cloud computing, edge and embedded edge cloud computing, multi-tenancy, network virtualization, neural networks, software-defined networking (SDN), virtualization, VLAN, VxLAN
Department
Electrical Engineering
Recommended Citation
Nader F. Mir. "AI-Assisted Edge Computing for Multi-Tenant Management of Edge Devices in 6G Networks" International Conference on 6G Networking, 6GNet 2023 (2023). https://doi.org/10.1109/6GNet58894.2023.10317735
