Enhancing Data Collection in Wide-Area Internet of Things: A Comprehensive Low-Overhead Approach

The rapid development of the Internet of Things (IoT) has led to the widespread application of widearea IoT, which offers the advantages of low power consumption and wide coverage. Nevertheless, the scarcity of bandwidth resources poses a significant challenge to the data transmission efficiency of wide-area IoT. Furthermore, the data encoding algorithms currently employed for message payloads tend to exhibit high redundancy and low efficiency. In order to enhance the data transmission efficiency of widearea IoT, our research has yielded the following outcomes: (1) A Template-Based Data Encoding Algorithm (TempEncode) is proposed, which employs data templates to define the message structure. The data template is employed by both senders and receivers, enabling the message payload to be compressed and overhead reduced. (2), a Low Overhead and Enhancing Data Collection (LEAD) approach has been devised for wide-area IoT based on the Message Queuing Telemetry Transport (MQTT) protocol and integrating TempEncode with Robust Header Compression. The experimental results demonstrate that LEAD has reduced the packet size by approximately 50.2% on average in comparison to the original MQTT protocol, thereby achieving efficient data transmission performance.