Application-Aware Real-Time Network Resource Allocation for Industry 5.0

Industry 5.0 integrates advanced technologies like Automated Guided Vehicles (AGVs) and Augmented/Virtual Reality (AR/VR) with human expertise, requiring ultra-reliable communication for safe and efficient manufacturing. Network resource allocation in this context is challenging, demanding efficient support for diverse applications while meeting stringent performance targets, including 99.9999% availability. This study presents a novel application-aware resource allocation scheme for an Industry 5.0 system connected to a 5G network. Our approach dynamically adapts to industrial application states, bridging network optimization and real-time factory operations. The solution comprises (1) a learning-based framework for safety and productivity-conscious allocation policies, (2) a heuristic real-time resource allocation policy addressing the computational scalability problem of learning-based methods, and (3) statistical analysis for bandwidth requirement estimation. Simulation results show our method achieves 99.9999% availability while reducing bandwidth usage by nearly 50% compared to traditional methods. This work contributes to more efficient and scalable Industry 5.0 systems, potentially doubling the number of supported industrial components within the same network infrastructure.