Dictionary-Based DPCM Method for Compressing IoT Big Data

The sensor nodes in IoT are usually supplied by energy using batteries with limited capacity. Therefore, saving energy as much as possible is important for increasing their lifetime and thus allowing their use in real applications. Because radio communication is usually the major reason of energy consumption, among the most commonly adopted energy-saving methods is to reduce data transmission / reception, for example, by compressing data. Taking advantage of the high correlation which usually occurs between successive samples captured by IoT sensor nodes and using the entropy principle in compression, a simple lossless algorithm for compression built on Differential Pulse Code Modulation (DPCM) was suggested in this paper, that is especially useful for IoT sensor nodes that characterized by reduced memory and computational resources. Compared to the state-of-the-art approaches, the findings of our simulation experiments showed that the suggested solution substantially decreased the consumption of energy and enhanced the network lifetime for all sensor nodes.