A Price-and-Branch Algorithm for Network Slice Optimization in Packet-Switched Xhaul Access Networks

Abstract

Network slicing is a concept introduced in 5G networks that supports the provisioning of multiple types of mobile services with diversified quality of service (QoS) requirements in a shared network. Network slicing concerns the placement/allocation of radio processing resources and traffic flow transport over the Xhaul transport network—connecting the 5G radio access network (RAN) elements—for multiple services while ensuring the slices’ isolation and fulfilling specific service requirements. This work focuses on modeling and optimizing network slicing in packet-switched Xhaul networks, a cost-effective, flexible, and scalable transport solution in 5G RANs. The considered network scenario assumes two types of network slices related to enhanced mobile broadband (eMBB) and ultra-reliable low-latency communications (URLLC) services. We formulate a network slicing planning optimization problem and model it as a mixed-integer linear programming (MILP) problem. Moreover, we develop an efficient price-and-branch algorithm (PBA) based on column generation (CG). This advanced optimization technique allows for overcoming the MILP model’s poor performance when solving larger network problem instances. Using extensive numerical experiments, we show the advantages of the PBA regarding the quality of the solutions obtained and the computation times, and analyze the packet-switched Xhaul network’s performance in various network slicing scenarios.