Admission Control for 5G Core Network Slicing Based on Deep Reinforcement Learning-Reference-Cited by-同舟云学术

Admission Control for 5G Core Network Slicing Based on Deep Reinforcement Learning

Published:2022-09 Issue:3 Volume:16 Page:4686-4697
ISSN:1932-8184
Container-title:IEEE Systems Journal
language:
Short-container-title:IEEE Systems Journal

Author:

Villota-Jacome William F.¹^ORCID,Rendon Oscar Mauricio Caicedo²^ORCID,da Fonseca Nelson L. S.¹^ORCID

Affiliation:

1. Institute of Computing, University of Campinas, Campinas, Brazil

2. Telematics Engineering Group, Universidad del Cauca, Popayán, Colombia

Funder

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Conselho Nacional de Desenvolvimento Científico e Tecnológico

Sao Paulo Research Foundation

Universidad del Cauca

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Control and Systems Engineering,Computer Networks and Communications,Computer Science Applications,Information Systems

Link

http://xplorestaging.ieee.org/ielx7/4267003/9866865/09779742.pdf?arnumber=9779742

Reference30 articles.

1. Resource allocation in an NFV/SDN-based network architecture;herrera,2018

2. A Machine Learning Approach to 5G Infrastructure Market Optimization

3. Adaptive Interference-Aware VNF Placement for Service-Customized 5G Network Slices

4. Towards Efficiently Provisioning 5G Core Network Slice Based on Resource and Topology Attributes

5. VNF Placement and Resource Allocation for the Support of Vertical Services in 5G Networks

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