Enhancing 5G V-RAN Reliability via Reactive CU-UP Scaling

The 5th generation and beyond of cellular networks ($5 \mathrm{G}\quad ~\mathrm{B} 5 \mathrm{G}$) adopted a cloud-based architecture, representing a significant evolution compared to monolithic approaches of previous generations. This transformation has even been devised for the Radio Access Network (RAN), with the Cloud-RAN (C-RAN), and its virtualized version the Virtual RAN (VRAN) as crucial and key components. RAN cloudification has added up to the flexibility, reduced deployment and operational costs for the network operators. The high-speed demands, vast volumes of data, and the low latency response requirements of future applications (e.g. V2X, IoT, URLLC, and others) create significant stress on some V-RAN components. In the V-RAN architecture, the CU-UP is highlighted as the datapath bottleneck of the V-RAN under high traffic loads. This paper aims to enhance the reliability of 5G V-RAN by addressing the bottleneck issues of CU-UP by developing a controller that performs reactive horizontal scaling of the CU-UP component. The scaling mechanism is driven by an algorithm that estimates CPU usage based on a Linear Regression model, based on the rate of incoming packets, with the goal to increase the overall 5G network performance delivered to the end users. Using real-world traffic patterns, we tested the proposed scaling mechanism, conducting the experiments in a non-simulated realworld testbeds exposing our system to dynamic conditions. Our findings highlight the importance of adapting such a scaling mechanism to ensure the robust reliability of the 5G V-RAN.