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Resource allocation modeling for fine-granular network slicing in beyond 5G systems

Shu, Zhaogang; Taleb, Tarik; Song, Jaeseung (2022-04-01)

 
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URL:
https://doi.org/10.1587/transcom.2021WWI0002

Shu, Zhaogang
Taleb, Tarik
Song, Jaeseung
Institute of Electronics
01.04.2022

Shu, Z., Taleb, T., & Song, J. (2022). Resource allocation modeling for fine-granular network slicing in beyond 5g systems. IEICE Transactions on Communications, E105.B(4), 349–363. https://doi.org/10.1587/transcom.2021WWI0002

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Copyright © 2022 The Institute of Electronics, Information and Communication Engineers.
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doi:https://doi.org/10.1587/transcom.2021WWI0002
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https://urn.fi/URN:NBN:fi-fe2023051143449
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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.

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