This review synthesizes research on the impact of blocking delay on microcontroller speed and responsiveness in IoT devices for industrial automation. It evaluates blocking delay effects on microcontroller performance. The review benchmarks scheduling and edge computing techniques, identifies mitigation strategies, compares case study outcomes, and analyzes architectural and software factors influencing blocking delay. A systematic analysis of experimental, simulation, and co-design studies was conducted. The analysis focused on real-time scheduling, interrupt handling, network-induced latency, and edge computing integration. Key findings reveal that advanced scheduling algorithms and interrupt nesting significantly reduce blocking delays and improve task responsiveness. Edge computing and hardware optimizations also minimize network-induced latency and enhance local processing capabilities. Multiple sources of blocking delay, including resource contention and network overload, are mitigated through adaptive scheduling and hardware-assisted mechanisms. Real-world case studies confirm substantial latency reductions and improved control performance in industrial IoT contexts. These findings underscore the interplay of software and hardware factors in shaping microcontroller responsiveness. The review highlights the necessity for scalable, integrated solutions that address dynamic industrial environments. It informs the design of more responsive and efficient microcontroller-based IoT systems for industrial automation.
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