Title: A Federated Edge-Cloud Architecture for Autonomous Logistics Systems: Enabling Real-Time Coordination and Energy Efficiency
Authors: Thar Htet Min and Adam Kargbo
Volume: 9
Issue: 8
Pages: 50-62
Publication Date: 2025/08/28
Abstract:
The growing need for autonomous technologies and real-time decision-making is propelling the logistics sector's rapid digital transformation. In order to improve autonomous logistics systems' scalability, security, and energy efficiency, this article suggests a federated edge-cloud architecture. The architecture decentralises data processing by combining edge computing and federated learning, which lowers latency and protects privacy by preventing the transport of raw data to central servers. To improve global learning models, local edge devices execute model updates that are safely aggregated in the cloud. A tri-layered architecture that combines cloud orchestration and edge autonomy, battery-aware dynamic routing for energy optimisation, and federated anomaly detection to provide resilience against disruptions are some of the main achievements. According to experimental evaluation, delivery times can be shortened by up to 35% and energy usage can be decreased by 30%. Future developments like blockchain-enabled trust and 6G-driven smart logistics are covered in the paper's conclusion.