Split-Compression Framework for Traffic Reduction Between IoT and Cloud

The proliferation of Internet of Things (IoT) devices has led to an exponential increase in data generation, resulting in significant network congestion and latency issues between IoT devices and cloud infrastructure. To mitigate these challenges, this research proposes a data compression framework designed to reduce network traffic and enhance data transmission efficiency between IoT devices and the cloud. Our approach leverages advanced compression algorithms and machine learning technique (autoencoder) to minimize data size while preserving data integrity and accuracy. Experimental results demonstrate 80 % reduction in size using our custom split framework comparing it with no compression and more than 45 % than standard compression methods.