An Unified Data Compression Framework in an IoT Network: Towards Performance Improvement - Kumar R.; Pandey O.J.; Hegde R.M. (My University, 2025)
The Internet of Things (IoT) has fundamentally changed the way we interact worldwide, however, the sheer volume of data it generates is enormous. Effectively handling this extensive data is a critical task in IoT networks, as transmitting it over the network consumes significant energy. Therefore, the need for data compression at the sensor layer and gateways directly improves the data transmission latency and network bandwidth requirements, preserving considerable energy. In this study, we propose a novel and unified data compression method based on a predictive encoding scheme at the sensor layer and a lossy dimensional reduction framework at the gateway level. The framework involves different stages of data pre-processing, including smoothing, quantization, and encoding, and the final stage involves the utilization of dimension reduction techniques to compress the data as a consequence, we achieve an overall reduction in energy consumption over the network. The performance of the proposed methods is evaluated using real field sensory data. Here, the performance is evaluated in terms of the obtained compression factor and the energy consumed by the network. Finally, the obtained results demonstrate the effectiveness of the proposed method when compared to existing methods in the literature. © 2023 IEEE.