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Resource Provisioning and Utilization in 5G Network Slicing: A Survey of Recent Advances, Challenges, and Open Issues


Affiliations
1 Department of Telecommunication Engineering, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
 

The increasing demands for higher bandwidth and lower latency in modern telecommunications networks have led to the exploration of network slicing as a means to meet these requirements more efficiently in next-generation 5G networks. Despite substantial academic interest in resource allocation and management in network slicing, existing research is dispersed and fragmented. This study presents a categorization and assessment of the latest research on resource allocation and optimization techniques in 5G network slicing. It also shows how advanced machine learning techniques can support resource management in sliced wireless networks. The present paper offers a complete overview and analysis of current solutions for resource allocation and management in 5G network slicing, outlines open research challenges, and suggests future research directions for researchers and engineers in this field.

Keywords

Network Slicing, Resource Allocation, 5G Network, Management, Optimization, SDN, NFV.
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  • Resource Provisioning and Utilization in 5G Network Slicing: A Survey of Recent Advances, Challenges, and Open Issues

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Authors

Simon Atuah Asakipaam
Department of Telecommunication Engineering, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
Jerry John Kponyo
Department of Telecommunication Engineering, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
Kwame Oteng Gyasi
Department of Telecommunication Engineering, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana

Abstract


The increasing demands for higher bandwidth and lower latency in modern telecommunications networks have led to the exploration of network slicing as a means to meet these requirements more efficiently in next-generation 5G networks. Despite substantial academic interest in resource allocation and management in network slicing, existing research is dispersed and fragmented. This study presents a categorization and assessment of the latest research on resource allocation and optimization techniques in 5G network slicing. It also shows how advanced machine learning techniques can support resource management in sliced wireless networks. The present paper offers a complete overview and analysis of current solutions for resource allocation and management in 5G network slicing, outlines open research challenges, and suggests future research directions for researchers and engineers in this field.

Keywords


Network Slicing, Resource Allocation, 5G Network, Management, Optimization, SDN, NFV.

References





DOI: https://doi.org/10.22247/ijcna%2F2023%2F220736