Large Scale Network

Large-scale network analysis focuses on understanding and optimizing the structure and function of massive interconnected systems, aiming to improve efficiency, resilience, and performance. Current research emphasizes developing scalable algorithms and model architectures, such as graph neural networks and autoencoders, to efficiently analyze these networks and predict their behavior, often incorporating techniques from machine learning and reinforcement learning. This field is crucial for advancements in diverse areas, including wireless communication, traffic management, social network analysis, and power grid optimization, enabling data-driven decision-making and improved resource allocation in complex systems.