Journal
IEEE COMMUNICATIONS MAGAZINE
Volume 58, Issue 6, Pages 32-38Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/MCOM.001.1900653
Keywords
Artificial intelligence; Admission control; Network slicing; Resource management; Dynamic scheduling; Heuristic algorithms; Task analysis
Funding
- H2020 5G-TOURS project [856950]
- H2020 5GROWTH project [856709]
- ANR CANCAN project [ANR18-CE25-0011]
Ask authors/readers for more resources
Network slicing is an emerging paradigm in mobile networks that leverages NFV to enable the instantiation of multiple virtual networks -- named slices -- over the same physical network infrastructure. The operator can allocate to each slice dedicated resources and customized functions that allow meeting the highly heterogeneous and stringent requirements of modern mobile services. Managing functions and resources under network slicing is a challenging task that requires making efficient decisions at all network levels, in some cases even in real time, which can be achieved by integrating artificial intelligence (AI) in the network. We outline a general framework for AI-based network slice management, introducing AI in the different phases of the slice life cycle, from admission control to dynamic resource allocation in the network core and at the radio access. A sensible use of AI for network slicing results in strong benefits for the operator, with expected performance gains between 25 and 80 percent in representative case studies.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available