Bandwidth Allocation

Bandwidth allocation research focuses on optimizing the distribution of network resources to maximize efficiency and fairness in various applications, particularly in distributed machine learning (like federated learning) and wireless communication systems. Current research employs diverse approaches, including dynamic programming, convex optimization, graph neural networks, and reinforcement learning, to address challenges such as heterogeneity in user demands and channel conditions, and to achieve goals like faster convergence and improved fairness. These advancements are crucial for improving the performance and scalability of emerging technologies reliant on efficient resource management, impacting fields ranging from wireless networking to artificial intelligence.