End-to-End Slicing With Optimized Communication and Computing Resource Allocation in Multi-Tenant 5G Systems

被引:43
|
作者
Chien, Hsu-Tung [1 ]
Lin, Ying-Dar [1 ]
Lai, Chia-Lin [2 ,3 ]
Wang, Chien-Ting [4 ,5 ]
机构
[1] Natl Chiao Tung Univ, Dept Comp Sci, Hsinchu 300, Taiwan
[2] Ind Technol Res Inst, Informat & Commun Res Lab, Hsinchu 300, Taiwan
[3] MediaTek Inc, Hsinchu 30078, Taiwan
[4] Natl Chiao Tung Univ, Grad Degree Program Network & Informat Syst, Hsinchu 300, Taiwan
[5] Acad Sinica, Taipei 115, Taiwan
基金
欧盟地平线“2020”;
关键词
Radio Access Network (RAN); Multi-access Edge Computing (MEC); slicing; computing resource; communication resource; virtualization; optimization; NETWORK;
D O I
10.1109/TVT.2019.2959193
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Slicing is a key technology in 5G networks to provide scalability and flexibility in allocating computing and communication resources among multiple tenants. Typically, 5G networks have a 2-tier architecture consisting of a central office and transport network in the upper tier and a multi-access edge and radio access network in the lower tier. The tenants which share the 2-tier architecture typically have different service-dependent resource requirements. This study proposes an algorithm, designated as Upper-tier First with Latency-bounded Over-provisioning Prevention (UFLOP), to adjust the capacity and traffic allocation in such a way as to minimize the "over-provisioning ratio" while still satisfying the latency constraints and Service Level Agreements (SLAs) of the tenants. The performance of UFLOP is evaluated experimentally with a real testbed on an end-to-end slicing framework using three typical 5G services, namely Enhanced Mobile Broadband (eMBB), Ultra-Reliable Low Latency (URLLC), and massive Machine Type Connection (mMTC). It is shown that UFLOP successfully determines the critical traffic allocation ratio between the central office and the edge which achieves an over-provisioning ratio close to zero while still meeting the latency requirements. The results suggest optimal resource allocation ratios of 10:0, 1.5:8.5 and 7.8:2.2 for the eMBB, URLLC and mMTC applications, respectively. Furthermore, it is shown that the computing resource behaves as a bottleneck for the eMBB and mMTC services, while the communication resource serves as a bottleneck for the URLLC service.
引用
收藏
页码:2079 / 2091
页数:13
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