Orchestrating Services with QoS Assurance at the Edge of Virtualized 5G Networks

Abstract

This work investigates the computational footprint of containerized 5G components deployed on a virtualized infrastructure, and leverages this profiling to propose an intelligent orchestration mechanism to maximize both the capacity offered to mobile network users and resource availability to application level services deployed on the computing infrastructure. We deployed and configured containerized 5G core network and radio access components using Open5GCore and UERANSIM, analyzing their resource occupation on the host server. The results show that the User Plane Function and the virtualized gNodeB introduce the most significant processing overhead. For instance, as the system scales from 5 users with 5 Mbps channels to 100 users with 50 Mbps channels, we observe an increase in CPU utilization of approximately 522%, highlighting the strong dependency between traffic load and resource consumption. Then, we incorporate the measured resource profiles into a state-of-the-art service orchestration system capable of deploying both 5G core network components and application-level services on heterogeneous computing equipment. Using an appropriate simulation tool, we evaluate our intelligent scheduling algorithm for service placement and compare it with relevant heuristic strategies. Results demonstrate that the proposed approach reduces service blocking probability by up to 76.77% while improving the bandwidth delivered to users by up to 46.76%, depending on service arrival rates and the number of users connected to the network. Based on these findings, we conclude that the proposed approach proves helpful in improving both resource efficiency and service quality.