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Resource Allocation Modeling for Fine-Granular Network Slicing in Beyond 5G Systems
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Through the concept of network slicing, a single physical network infrastructure can be split into multiple logically-independent Network Slices (NS), each of which is customized for the needs of its respective individual user or industrial vertical. In the beyond 5G (B5G) system, this customization can be done for many targeted services, including, but not limited to, 5G use cases and beyond 5G. The network slices should be optimized and customized to stitch a suitable environment for targeted industrial services and verticals. This paper proposes a novel Quality of Service (QoS) framework that optimizes and customizes the network slices to ensure the service level agreement (SLA) in terms of end-to-end reliability, delay, and bandwidth communication. The proposed framework makes use of network softwarization technologies, including software-defined networking (SDN) and network function virtualization (NFV), to preserve the SLA and ensure elasticity in managing the NS. This paper also mathematically models the end-to-end network by considering three parts: radio access network (RAN), transport network (TN), and core network (CN). The network is modeled in an abstract manner based on these three parts. Finally, we develop a prototype system to implement these algorithms using the open network operating system (ONOS) as a SDN controller. Simulations are conducted using the Mininet simulator. The results show that our QoS framework and the proposed resource allocation algorithms can effectively schedule network resources for various NS types and provide reliable E2E QoS services to end-users.
- Publication
- IEICE TRANSACTIONS on Communications Vol.E105-B No.4 pp.349-363
- Publication Date
- 2022/04/01
- Publicized
- 2021/10/19
- Online ISSN
- 1745-1345
- DOI
- 10.1587/transcom.2021WWI0002
- Type of Manuscript
- Special Section INVITED PAPER (Special Section on Wired-and-Wireless Network System Technologies in Beyond 5G Era)
- Category
Authors
Zhaogang SHU
Fujian Agriculture and Forestry University
Tarik TALEB
The University of Oulu
Jaeseung SONG
Sejong University
Keyword
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Zhaogang SHU, Tarik TALEB, Jaeseung SONG, "Resource Allocation Modeling for Fine-Granular Network Slicing in Beyond 5G Systems" in IEICE TRANSACTIONS on Communications,
vol. E105-B, no. 4, pp. 349-363, April 2022, doi: 10.1587/transcom.2021WWI0002.
Abstract: Through the concept of network slicing, a single physical network infrastructure can be split into multiple logically-independent Network Slices (NS), each of which is customized for the needs of its respective individual user or industrial vertical. In the beyond 5G (B5G) system, this customization can be done for many targeted services, including, but not limited to, 5G use cases and beyond 5G. The network slices should be optimized and customized to stitch a suitable environment for targeted industrial services and verticals. This paper proposes a novel Quality of Service (QoS) framework that optimizes and customizes the network slices to ensure the service level agreement (SLA) in terms of end-to-end reliability, delay, and bandwidth communication. The proposed framework makes use of network softwarization technologies, including software-defined networking (SDN) and network function virtualization (NFV), to preserve the SLA and ensure elasticity in managing the NS. This paper also mathematically models the end-to-end network by considering three parts: radio access network (RAN), transport network (TN), and core network (CN). The network is modeled in an abstract manner based on these three parts. Finally, we develop a prototype system to implement these algorithms using the open network operating system (ONOS) as a SDN controller. Simulations are conducted using the Mininet simulator. The results show that our QoS framework and the proposed resource allocation algorithms can effectively schedule network resources for various NS types and provide reliable E2E QoS services to end-users.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.2021WWI0002/_p
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@ARTICLE{e105-b_4_349,
author={Zhaogang SHU, Tarik TALEB, Jaeseung SONG, },
journal={IEICE TRANSACTIONS on Communications},
title={Resource Allocation Modeling for Fine-Granular Network Slicing in Beyond 5G Systems},
year={2022},
volume={E105-B},
number={4},
pages={349-363},
abstract={Through the concept of network slicing, a single physical network infrastructure can be split into multiple logically-independent Network Slices (NS), each of which is customized for the needs of its respective individual user or industrial vertical. In the beyond 5G (B5G) system, this customization can be done for many targeted services, including, but not limited to, 5G use cases and beyond 5G. The network slices should be optimized and customized to stitch a suitable environment for targeted industrial services and verticals. This paper proposes a novel Quality of Service (QoS) framework that optimizes and customizes the network slices to ensure the service level agreement (SLA) in terms of end-to-end reliability, delay, and bandwidth communication. The proposed framework makes use of network softwarization technologies, including software-defined networking (SDN) and network function virtualization (NFV), to preserve the SLA and ensure elasticity in managing the NS. This paper also mathematically models the end-to-end network by considering three parts: radio access network (RAN), transport network (TN), and core network (CN). The network is modeled in an abstract manner based on these three parts. Finally, we develop a prototype system to implement these algorithms using the open network operating system (ONOS) as a SDN controller. Simulations are conducted using the Mininet simulator. The results show that our QoS framework and the proposed resource allocation algorithms can effectively schedule network resources for various NS types and provide reliable E2E QoS services to end-users.},
keywords={},
doi={10.1587/transcom.2021WWI0002},
ISSN={1745-1345},
month={April},}
Copy
TY - JOUR
TI - Resource Allocation Modeling for Fine-Granular Network Slicing in Beyond 5G Systems
T2 - IEICE TRANSACTIONS on Communications
SP - 349
EP - 363
AU - Zhaogang SHU
AU - Tarik TALEB
AU - Jaeseung SONG
PY - 2022
DO - 10.1587/transcom.2021WWI0002
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E105-B
IS - 4
JA - IEICE TRANSACTIONS on Communications
Y1 - April 2022
AB - Through the concept of network slicing, a single physical network infrastructure can be split into multiple logically-independent Network Slices (NS), each of which is customized for the needs of its respective individual user or industrial vertical. In the beyond 5G (B5G) system, this customization can be done for many targeted services, including, but not limited to, 5G use cases and beyond 5G. The network slices should be optimized and customized to stitch a suitable environment for targeted industrial services and verticals. This paper proposes a novel Quality of Service (QoS) framework that optimizes and customizes the network slices to ensure the service level agreement (SLA) in terms of end-to-end reliability, delay, and bandwidth communication. The proposed framework makes use of network softwarization technologies, including software-defined networking (SDN) and network function virtualization (NFV), to preserve the SLA and ensure elasticity in managing the NS. This paper also mathematically models the end-to-end network by considering three parts: radio access network (RAN), transport network (TN), and core network (CN). The network is modeled in an abstract manner based on these three parts. Finally, we develop a prototype system to implement these algorithms using the open network operating system (ONOS) as a SDN controller. Simulations are conducted using the Mininet simulator. The results show that our QoS framework and the proposed resource allocation algorithms can effectively schedule network resources for various NS types and provide reliable E2E QoS services to end-users.
ER -
English
