Resources allocation for hybrid cloud-edge computing in 5G network slicing

Abstract

In typical heterogeneous networks such as 5G and beyond, innovative technologies such as edge computing and network slicing can enhance overall network performance in terms of handling critical mission services as they often require extremely low latencies. Notably, network slicing facilitates the provisioning of virtual slices with different characteristics to serve different end-user requirements. The Network operator achieves this goal by utilizing the already existing physical wireless network resource. Current resource provisioning schemes suffer inadequacies in scalability and flexibility Thus to support both Cloud and Edge Computing in 5G and beyond networking, the work herein proposes a novel low latency scheme that affords dynamic and intelligent allocation of multi-dimensional resources. It bases on a Hybrid Cloud-edge Network Slicing (HCENS) architecture on leveraging both Cloud and Edge Computing The proposed scheme creates a flexible, scalable as well as energy efficient resource provisioning. Its architecture comprises both centralized units (CUs) and distributed units (DUs). These provide storage, that in turn enhances function partitioning for various network slices. Several agent-based simulations scenarios are carried out in evaluating the efficacy of the proposed scheme. Obtained analytical and simulation results indicate drastic reductions in network latencies for critical mission end user services. This couples with reductions in storage requirements.