A Comparative Analysis of Edge and Cloud Architectures for Real-Time Industrial Control Systems

Traditional Industrial Control System architectures that rely on sending raw sensor data to a centralized cloud face three critical challenges: high latency, unreliability upon connection loss, and massive data traffic costs. For real-time control loops, this latency is unacceptable. This paper analyzes the «Edge Computing» paradigm as a solution. This approach involves moving computational tasks from the distant cloud directly «to the edge» of the network – onto local gateways or industrial controllers on the factory floor. Instead of transmitting gigabytes of raw streams, the Edge device processes data locally, sending only valuable, processed results to the cloud. The analysis demonstrates that Edge Computing radically reduces latency to the millisecond level, ensures autonomous system operation during connectivity failure, and significantly conserves network bandwidth. This makes Edge Computing a key enabling technology for building responsive, resilient, and scalable Cyber-Physical Systems.