Multi-Access Edge Computing Resource Slice Allocation: A Review
The global deployment of fifth generation mobile cellular (5G) and beyond (5GB) communication systems has accelerated the growth of the Internet of Things (IoT) and the Internet of Everything (IoE). New applications and services that add complexity to the network, and require low latency, have neces...
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2024-01-01
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| Online Access: | https://ieeexplore.ieee.org/document/10792437/ |
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| author | Faezeh Bahramisirat Mark A. Gregory Shuo Li |
| author_facet | Faezeh Bahramisirat Mark A. Gregory Shuo Li |
| author_sort | Faezeh Bahramisirat |
| collection | DOAJ |
| description | The global deployment of fifth generation mobile cellular (5G) and beyond (5GB) communication systems has accelerated the growth of the Internet of Things (IoT) and the Internet of Everything (IoE). New applications and services that add complexity to the network, and require low latency, have necessitated new architectures that facilitate dynamic resource allocation. The network edge is changing, as Multi-Access Edge Computing (MEC) is deployed with new responsive designs that include dynamic resource slice allocation that supports the varying needs of new and innovative applications and services. Augmented reality, extended reality and virtual reality applications are key drivers for the changing network architecture. IoT and IoE data aggregation and analysis at the network edge has required new approaches to designing edge network architectures that achieve seamless access anywhere and anytime, ultra-low latency, edge computing and storage, and ultra-high bandwidth. MEC and Network Slicing (NS) are evolving to provide a key part of the solution to the new challenges. MEC allows operators to connect user devices to edge cloud computing and storage systems with low latency and high bandwidth. However, a practical configuration is required to facilitate cloud-based applications and services at the network edge and to address end-user demands. The MEC resources may be flexibly and dynamincally partitioned into separate slices. This paper will review how the integration of MEC and NS can be utilised for efficient resource allocation in edge networks. This article comprehensively reviewed the architecture of network slicing and edge computing. A review of MEC and NS in support of 5G and 5GB has been included and current challenges identified. This article aims to serve as an insightful guide to inspire further research into 5GB communication systems and edge computing. |
| format | Article |
| id | doaj-art-a3e4e37142864d6d97d38d032dc6ddd1 |
| institution | Kabale University |
| issn | 2169-3536 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-a3e4e37142864d6d97d38d032dc6ddd12024-12-18T00:02:51ZengIEEEIEEE Access2169-35362024-01-011218857218858910.1109/ACCESS.2024.351507710792437Multi-Access Edge Computing Resource Slice Allocation: A ReviewFaezeh Bahramisirat0https://orcid.org/0009-0004-8009-4736Mark A. Gregory1https://orcid.org/0000-0003-4631-6468Shuo Li2https://orcid.org/0000-0002-0357-8284School of Engineering, RMIT University, Melbourne, VIC, AustraliaSchool of Engineering, RMIT University, Melbourne, VIC, AustraliaSchool of Engineering, RMIT University, Melbourne, VIC, AustraliaThe global deployment of fifth generation mobile cellular (5G) and beyond (5GB) communication systems has accelerated the growth of the Internet of Things (IoT) and the Internet of Everything (IoE). New applications and services that add complexity to the network, and require low latency, have necessitated new architectures that facilitate dynamic resource allocation. The network edge is changing, as Multi-Access Edge Computing (MEC) is deployed with new responsive designs that include dynamic resource slice allocation that supports the varying needs of new and innovative applications and services. Augmented reality, extended reality and virtual reality applications are key drivers for the changing network architecture. IoT and IoE data aggregation and analysis at the network edge has required new approaches to designing edge network architectures that achieve seamless access anywhere and anytime, ultra-low latency, edge computing and storage, and ultra-high bandwidth. MEC and Network Slicing (NS) are evolving to provide a key part of the solution to the new challenges. MEC allows operators to connect user devices to edge cloud computing and storage systems with low latency and high bandwidth. However, a practical configuration is required to facilitate cloud-based applications and services at the network edge and to address end-user demands. The MEC resources may be flexibly and dynamincally partitioned into separate slices. This paper will review how the integration of MEC and NS can be utilised for efficient resource allocation in edge networks. This article comprehensively reviewed the architecture of network slicing and edge computing. A review of MEC and NS in support of 5G and 5GB has been included and current challenges identified. This article aims to serve as an insightful guide to inspire further research into 5GB communication systems and edge computing.https://ieeexplore.ieee.org/document/10792437/Network slicingmulti-access edge computing5G6Gresource allocationradio access network |
| spellingShingle | Faezeh Bahramisirat Mark A. Gregory Shuo Li Multi-Access Edge Computing Resource Slice Allocation: A Review IEEE Access Network slicing multi-access edge computing 5G 6G resource allocation radio access network |
| title | Multi-Access Edge Computing Resource Slice Allocation: A Review |
| title_full | Multi-Access Edge Computing Resource Slice Allocation: A Review |
| title_fullStr | Multi-Access Edge Computing Resource Slice Allocation: A Review |
| title_full_unstemmed | Multi-Access Edge Computing Resource Slice Allocation: A Review |
| title_short | Multi-Access Edge Computing Resource Slice Allocation: A Review |
| title_sort | multi access edge computing resource slice allocation a review |
| topic | Network slicing multi-access edge computing 5G 6G resource allocation radio access network |
| url | https://ieeexplore.ieee.org/document/10792437/ |
| work_keys_str_mv | AT faezehbahramisirat multiaccessedgecomputingresourcesliceallocationareview AT markagregory multiaccessedgecomputingresourcesliceallocationareview AT shuoli multiaccessedgecomputingresourcesliceallocationareview |