Edge Network

Edge networks aim to bring computation and data processing closer to data sources, improving latency and bandwidth efficiency for AI applications. Current research focuses on optimizing resource allocation and model architectures (e.g., hierarchical federated learning, deep equilibrium models) to address challenges like heterogeneity, security, and communication bottlenecks in these distributed systems. This field is significant because it enables privacy-preserving AI at scale, powering applications ranging from IoT devices to industrial automation and improving the efficiency and responsiveness of various AI-driven services.