Data Compression Algorithm for Wireless Sensor Networks

Energy consumption is a crucial problem affecting the lifetime of Wireless Sensor Networks (WSNs). In this research, we use data compression approach to reduce transmission data over wireless channels. A Distributed Wavelet Transform (DWT) is proposed for WSNs which is based on lifting scheme. The proposed scheme overcomes distributed wavelet algorithm issues such as time-consuming and calculation complexity. We use a Ring Topology based on Virtual Grid (VGRT) model that can effective eliminate spatial correlation in sensing data. Also in this paper, a novel data transmission mechanism named Data Selecting Mechanism (DSM) is designed to reduce the temporal correction in sensing data. It decreases the redundant data from its source, and cuts down the data needed for transmission. Simulation results are based on the Wavelet Lifting Transform (WLT) with DSM. Theoretically and experimentally, it is concluded that the proposed algorithm can reduce redundant data in WSNs efficiently and greatly decrease the energy consumption and prolongs the lifecycle. Keywords—Data Compression; Wavelet Lifting Transform; Data Selecting Mechanism