Demonstrating Smart Scaling of AI-Services for Future Networks

In this paper, we demonstrate a smart resource auto-scaling solution based on Multi-Agent Deep Reinforcement Learning (MADRL). Our decentralized approach dynamically adapts compute resources to services to ensure a smooth response to fluctuating user demands. The demonstration, consisting of a visualization and control dashboard, a cloud edge hardware configuration and an AI-based wireless fingerprinting service, shows in-place real-time scaling of resources in the virtual environment and its impact on service response time and performance.