LATENCY OPTIMIZATION IN 5G INDUSTRIAL IOT NETWORKS: TECHNIQUES AND PERFORMANCE ANALYSIS

The deployment of 5G in Industrial Internet of Things (IIoT) environments offers unprecedented opportunities for automation and real-time control. However, ultra-low latency remains a core requirement that centralized cloud architectures often fail to meet. This study investigates how latency in IIoT networks can be reduced by combining edge intelligence and network slicing. Using a simulated smart factory environment, the integration of local AI processing with dynamically allocated network slices shows a latency reduction of up to 45% compared to cloud-based systems. These results provide a scalable model for latency-sensitive IIoT applications in manufacturing, energy, and logistics.