Synchronization Parameter Update Barrier

Synchronization parameter update barriers hinder efficient distributed systems by creating bottlenecks in coordinating updates across multiple agents or nodes. Current research focuses on mitigating these barriers through techniques like asynchronous updates, dynamic synchronization triggers based on model variance, and novel algorithms such as Federated Dynamic Averaging and two-timescale synchronization frameworks. These advancements aim to improve the speed, scalability, and robustness of distributed systems in diverse applications, ranging from deep learning and robotics to digital twin networks and sensor synchronization.