Browsing by Author "Wang, Chien-Ting"

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End-to-End Slicing as a Service with Computing and Communication Resource Allocation for Multi-Tenant 5G Systems
(2019-10-01)
Chien, Hsu-Tung
;
Lin, Ying-Dar
;
Lai, Chia-Lin
;
Wang, Chien-Ting
;
交大名義發表
5G services, such as Ultra-reliable and Low Latency Communications, Massive Machine Type Communications and Enhanced Mobile Broadband, support low (or ultra-low) latency, a huge number of connections, and high bandwidth. Typically, 5G platforms are shared by multiple tenants, where each tenant has different service deployment requirements and thus requires different amounts of resources from the lower tier (i.e., radio access network and mobile edge) and upper tier (i.e., transport network and central office) of the 5G architecture. Consequently, slicing is a key technology in 5G networks for providing scalability and flexibility in allocating the 5G resources with appropriate isolation. This study proposes an Endto- End Slicing as a Service framework for slicing both computing and communication resources across the full 2-tier multi-access edge computing architecture. The framework is implemented using open source tools. It is shown that the framework successfully isolates the 5G resources, which are computing and communication, between slices (slicing isolation effect ratio equals 1) and ensures that resources of the deployed slices are merely sufficient to meet the latency requirements of the tenants. Moreover, the experiments show that URLLC and mMTC services require more than 70 percent of the needed computing and communication resources be provided by the edge and RAN in order to satisfy their tighter latency requirements. Overall, the results suggest a central to edge resource allocation ratio of 9:1, 3:7, and 1:9 for the eMBB, URLLC, mMTC applications, respectively. Therefore,
End-to-End Slicing With Optimized Communication and Computing Resource Allocation in Multi-Tenant 5G Systems
(2020-02-01)
Chien, Hsu-Tung
;
Lin, Ying-Dar
;
Lai, Chia-Lin
;
Wang, Chien-Ting
;
交大名義發表
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.