Network Flow

Network flow analysis focuses on understanding and optimizing the movement of data or objects through interconnected systems, with applications ranging from internet traffic management to multi-robot coordination. Current research emphasizes developing efficient algorithms, such as push-relabel methods and graph neural networks (GNNs), to analyze and predict network behavior, often incorporating machine learning for tasks like anomaly detection, traffic classification, and intrusion prevention. These advancements are crucial for improving network security, resource allocation, and the performance of complex systems, leading to more efficient and robust network infrastructures and applications.