Cloud Continuum

The cloud continuum represents a shift from centralized cloud computing to a distributed architecture integrating cloud, edge, and even in-network computing resources. Current research focuses on optimizing resource allocation and application placement across this heterogeneous environment, employing techniques like graph neural networks and reinforcement learning to manage the dynamic distribution of computational tasks and data. This approach aims to improve the efficiency, latency, and scalability of applications, particularly for data-intensive tasks like AI/ML model training and deployment in areas such as autonomous vehicles and real-time monitoring systems. The resulting advancements promise significant improvements in performance and resource utilization for a wide range of applications.