Prediction-Based End-to-End Dynamic Network Slicing in Hybrid Elastic Fiber-Wireless Networks

Abstract

In recent years, hybrid fiber-wireless (Fi-Wi) networks that integrate optical network technology and wireless communication technology have received widespread attention. The technical integration in Fi-Wi networks provides users with the possibility to establish high-quality connections that guarantee flexibility and economy. However, there are heterogeneous structures and resource types between the subnets of the Fi-Wi network. This article considers the segmented application of network slicing technology in the optical backbone and hybrid access parts of Fi-Wi networks. In this way, the seamless connection of wired and wireless networks can be realized, and meanwhile adapt to the multiple network service forms and differentiated service quality requirements introduced in the 5G network era. In this article, we design a dynamic slicing (PDSM) scheme based on traffic prediction. This scheme includes all four procedures of service provisioning, which are network slice creation, traffic prediction, online reconfiguration of network slices and intra-slice routing, and resource allocation based on the prediction results. It is more flexible than the traditional static slicing scheme in the scenario, where the network state changes dynamically. We develop a prediction-based dynamic slicing algorithm (PD-MSRA) with intra-slice multi-path routing and shared resource allocation for the entire workflow of PDSM. We evaluate the performance of PD-MSRA on a variety of network topologies, and also implement several comparison algorithms including static slicing strategies. Simulation results show that the PDSM scheme using PD-MSRA achieves low bandwidth blocking rate and the optimization of resource utilization.