Enhancing Cost-Effective 5G Virtualized RAN Pooling Gain on Clouds: An Intelligent Auto-Scaling Approach

Abstract

Cloud computing has revolutionized information technology (IT) infrastructure by providing benefits such as scalability, flexibility, and convenience. If the radio access networks of wireless systems are constructed on edge clouds, operators can obtain various advantages. One notable benefit is pooling gain achieved through auto-scaling, leading to savings on investment. However, conventional auto-scaling methods employ numerous instances to prevent traffic overloads and ensure reliable system performance during peak demand. This traditional approach increases the burden on computing resources. To address this, this paper introduces an intelligent auto-scaling scheme that enhances pooling gain by leveraging the distinctive attributes of cloud computing. Additionally, we refine pooling gain to measure the performance of the fifth generation (5G) base stations on edge clouds. The simulation outcomes of our advanced auto-scaling scheme demonstrate its ability to achieve substantial improvements in productivity compared to the simpler implementations used in distributed cell sites, both in terms of pooling gain and the efficient utilization of computing resources.

Keywords

• Cloud computing
• 5G virtualized base station
• pooling gain
• intelligent auto-scaling