Data Reduction Based on Compression Technique for Big Data in IoT

The data transmitting is very costly in the IoT sensor nodes and it wastes most of the energy. There are many techniques and concepts concerned with save of energy, mostly dedicated to minimize data transmission. Therefore, we can preserve considerable amount of energy with minimizing the data transmissions in networks of IoT sensor. In this research, we suggested a Data Reduction based on Compression Technique (DRCT) which works in the level of IoT sensor nodes. The DRCT includes two compression stages, a lossy SAX Quantization stage that reduces dynamic range of the sensor data readings, after that a lossless LZW compression to compress the output of the lossy quantization. OMNeT++ simulator along with a real sensory data gathered at Intel Lab are used to show the performance of the proposed method. The simulation experiments illustrate that the proposed DRCT technique provides a better performance than the other techniques in the literature.