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dc.contributor.authorChien, Hsu-Tungen_US
dc.contributor.authorLin, Ying-Daren_US
dc.contributor.authorLai, Chia-Linen_US
dc.contributor.authorWang, Chien-Tingen_US
dc.date.accessioned2020-05-05T00:02:23Z-
dc.date.available2020-05-05T00:02:23Z-
dc.date.issued2020-02-01en_US
dc.identifier.issn0018-9545en_US
dc.identifier.urihttp://dx.doi.org/10.1109/TVT.2019.2959193en_US
dc.identifier.urihttp://hdl.handle.net/11536/154194-
dc.description.abstractSlicing 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.en_US
dc.language.isoen_USen_US
dc.subjectRadio Access Network (RAN)en_US
dc.subjectMulti-access Edge Computing (MEC)en_US
dc.subjectslicingen_US
dc.subjectcomputing resourceen_US
dc.subjectcommunication resourceen_US
dc.subjectvirtualizationen_US
dc.subjectoptimizationen_US
dc.titleEnd-to-End Slicing With Optimized Communication and Computing Resource Allocation in Multi-Tenant 5G Systemsen_US
dc.typeArticleen_US
dc.identifier.doi10.1109/TVT.2019.2959193en_US
dc.identifier.journalIEEE TRANSACTIONS ON VEHICULAR TECHNOLOGYen_US
dc.citation.volume69en_US
dc.citation.issue2en_US
dc.citation.spage2079en_US
dc.citation.epage2091en_US
dc.contributor.department交大名義發表zh_TW
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentNational Chiao Tung Universityen_US
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.identifier.wosnumberWOS:000519957800075en_US
dc.citation.woscount0en_US
Appears in Collections:Articles