Optimizing Robot API Connections for Multimedia Data Transmission: A Federated Learning Approach

Abstract

This paper explores optimal methods for robots to connect with API services when handling video streaming, large image transfers, and other high-bandwidth data exchanges. We evaluate traditional centralized approaches against emerging federated learning architectures, comparing performance metrics including latency, bandwidth efficiency, data privacy, and computational overhead.