Compression-based Data Reduction Technique for IoT Sensor Networks

Energy savings are very common in IoT sensor networks because nodes operate with their own limited battery. The data transmission the is costly and consume much of energy while usage for processing considerably lower. There several energy-saving strategies principles, mainly dedicated to reducing data. Therefore, minimizing transfers networks, can conserve a considerable amount energy. In this research, Compression-Based Data Reduction (CBDR) technique was suggested which works level nodes. CBDR includes two stages compression, lossy SAX Quantization stage reduces dynamic range readings, after lossless LZW compression compress loss quantization output. Quantizing node readings down alphabet size results lowering, advantage best sizes, contributes greater from end things. Also, another improvement add Dynamic Transmission (DT-CBDR) decrease both total number sent gateway required. OMNeT++ simulator along real sensory gathered at Intel Lab used show performance proposed technique. simulation experiments illustrate that provides better than other techniques literature.