Efficient Large-Scale IoT Network: Integrating Asynchronous Communication and Huffman Coding in LoRa/PLC Systems

As Internet of Things (IoT) deployments expand, the development of sustainable and intelligent communication architectures is critical for managing large-scale device integration and high concurrency. This paper presents an innovative approach to enhance IoT network performance in LoRa and Power Line Communication systems through the integration of asynchronous communication, a user behavior-based Huffman coding method, and edge computing. Our multilevel architecture leverages gateways to efficiently monitor and control sensors and actuators, while our dynamic Huffman coding compresses frequently used commands based on user behavior, reducing energy consumption and improving data transmission efficiency. Edge computing facilitates local data preprocessing and real-time monitoring, enabling intelligent decision making and minimizing redundant cloud data transfers. Preliminary simulations demonstrate significant improvements in network efficiency, confirming the efficacy of our integrated approach for large-scale, intelligent, and sustainable IoT deployments.