Network Slicing for Beyond 5G Systems: An Overview of the Smart Port Use Case
As the idea of a new wireless communication standard (5G) started to circulate around the world, there was much speculation regarding its performance, making it necessary to carry out further research by keeping in view the challenges presented by it. 5G is considered a multi-system support network...
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2021-05-01
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doaj-03c2f16097204f269337eec79704112e2021-05-31T23:13:09ZengMDPI AGElectronics2079-92922021-05-01101090109010.3390/electronics10091090Network Slicing for Beyond 5G Systems: An Overview of the Smart Port Use CaseRana Muhammad Sohaib0Oluwakayode Onireti1Yusuf Sambo2Muhammad Ali Imran3James Watt School of Engineering, University of Glasgow, Glasgow G12 8QQ, UKJames Watt School of Engineering, University of Glasgow, Glasgow G12 8QQ, UKJames Watt School of Engineering, University of Glasgow, Glasgow G12 8QQ, UKJames Watt School of Engineering, University of Glasgow, Glasgow G12 8QQ, UKAs the idea of a new wireless communication standard (5G) started to circulate around the world, there was much speculation regarding its performance, making it necessary to carry out further research by keeping in view the challenges presented by it. 5G is considered a multi-system support network due to its ability to provide benefits to vertical industries. Due to the wide range of devices and applications, it is essential to provide support for massively interconnected devices. Network slicing has emerged as the key technology to meet the requirements of the communications network. In this paper, we present a review of the latest achievements of 5G network slicing by comparing the architecture of The Next Generation Mobile Network Alliance’s (NGMN’s) and 5G-PPP, using the enabling technologies software-defined networking (SDN) and network function virtualization (NFV). We then review and discuss machine learning (ML) techniques and their integration with network slicing for beyond 5G networks and elaborate on how ML techniques can be useful for mobility prediction and resource management. Lastly, we propose the use case of network slicing based on ML techniques in a smart seaport environment, which will help to manage the resources more efficiently.https://www.mdpi.com/2079-9292/10/9/10905GNGMN5G-PPPSDNNFVNS |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Rana Muhammad Sohaib Oluwakayode Onireti Yusuf Sambo Muhammad Ali Imran |
spellingShingle |
Rana Muhammad Sohaib Oluwakayode Onireti Yusuf Sambo Muhammad Ali Imran Network Slicing for Beyond 5G Systems: An Overview of the Smart Port Use Case Electronics 5G NGMN 5G-PPP SDN NFV NS |
author_facet |
Rana Muhammad Sohaib Oluwakayode Onireti Yusuf Sambo Muhammad Ali Imran |
author_sort |
Rana Muhammad Sohaib |
title |
Network Slicing for Beyond 5G Systems: An Overview of the Smart Port Use Case |
title_short |
Network Slicing for Beyond 5G Systems: An Overview of the Smart Port Use Case |
title_full |
Network Slicing for Beyond 5G Systems: An Overview of the Smart Port Use Case |
title_fullStr |
Network Slicing for Beyond 5G Systems: An Overview of the Smart Port Use Case |
title_full_unstemmed |
Network Slicing for Beyond 5G Systems: An Overview of the Smart Port Use Case |
title_sort |
network slicing for beyond 5g systems: an overview of the smart port use case |
publisher |
MDPI AG |
series |
Electronics |
issn |
2079-9292 |
publishDate |
2021-05-01 |
description |
As the idea of a new wireless communication standard (5G) started to circulate around the world, there was much speculation regarding its performance, making it necessary to carry out further research by keeping in view the challenges presented by it. 5G is considered a multi-system support network due to its ability to provide benefits to vertical industries. Due to the wide range of devices and applications, it is essential to provide support for massively interconnected devices. Network slicing has emerged as the key technology to meet the requirements of the communications network. In this paper, we present a review of the latest achievements of 5G network slicing by comparing the architecture of The Next Generation Mobile Network Alliance’s (NGMN’s) and 5G-PPP, using the enabling technologies software-defined networking (SDN) and network function virtualization (NFV). We then review and discuss machine learning (ML) techniques and their integration with network slicing for beyond 5G networks and elaborate on how ML techniques can be useful for mobility prediction and resource management. Lastly, we propose the use case of network slicing based on ML techniques in a smart seaport environment, which will help to manage the resources more efficiently. |
topic |
5G NGMN 5G-PPP SDN NFV NS |
url |
https://www.mdpi.com/2079-9292/10/9/1090 |
work_keys_str_mv |
AT ranamuhammadsohaib networkslicingforbeyond5gsystemsanoverviewofthesmartportusecase AT oluwakayodeonireti networkslicingforbeyond5gsystemsanoverviewofthesmartportusecase AT yusufsambo networkslicingforbeyond5gsystemsanoverviewofthesmartportusecase AT muhammadaliimran networkslicingforbeyond5gsystemsanoverviewofthesmartportusecase |
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