EndtoEnd Slicing With Optimized Communication and Computing Resource Allocation in MultiTenant 5G Systems 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 2tier architecture consisting of a central office and transport network in the upper tier and a multiaccess edge and radio access network in the lower tier. The tenants which share the 2tier architecture typically have different servicedependent resource requirements. This study proposes an algorithm, designated as Uppertier First with Latencybounded Overprovisioning Prevention (UFLOP), to adjust the capacity and traffic allocation in such a way as to minimize the xe2x80x9coverprovisioning ratioxe2x80x9d 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 endtoend slicing framework using three typical 5G services, namely Enhanced Mobile Broadband (eMBB), UltraReliable 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 overprovisioning 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.

Slicing Resource Allocation for eMBB and URLLC in 5G RAN This paper investigates the network slicing in the virtualized wireless network. We consider a downlink orthogonal frequency division multiple access system in which physical resources of base stations are virtualized and divided into enhanced mobile broadband (eMBB) and ultrareliable low latency communication (URLLC) slices. We take the network slicing technology to solve the problems of network spectral efficiency and URLLC reliability. A mixedinteger programming problem is formulated by maximizing the spectral efficiency of the system in the constraint of usersxe2x80x99 requirements for two slices, i.e., the requirement of the eMBB slice and the requirement of the URLLC slice with a high probability for each user. By transforming and relaxing integer variables, the original problem is approximated to a convex optimization problem. Then, we combine the objective function and the constraint conditions through dual variables to form an augmented Lagrangian function, and the optimal solution of this function is the upper bound of the original problem. In addition, we propose a resource allocation algorithm that allocates the network slicing by applying the Powellxe2x80x93Hestenesxe2x80x93Rockafellar method and the branch and bound method, obtaining the optimal solution. The simulation results show that the proposed resource allocation algorithm can significantly improve the spectral efficiency of the system and URLLC reliability, compared with the adaptive particle swarm optimization (APSO), the equal power allocation (EPA), and the equal subcarrier allocation (ESA) algorithm. Furthermore, we analyze the spectral efficiency of the proposed algorithm with the usersxe2x80x99 requirements change of two slices and get better spectral efficiency performance.