Energy- Efficient Clustering Schema Based on Data Reduction
Abstractــــ Wireless Sensor Networks (WSNs) typically have been consumed high energy in monitoring and radio communication trends. Furthermore, data diffusion modes in WSN typically generate errors such as noisy values, incorrect measurements or missing information, which minimize the standard of performance in such dynamic systems. In this article, we will present a Clustered Data Reduction Model (CDRM) at both sensor node level and cluster head level, which aims to reduce data transfer rates, and reach energy more effectively. Compared to the state-of-the-art statistical methods, the proposed CDRM reduced the rate of data transmission to ~ 18 %, and it slashed the energy consumption to ~ 98 % throughout the dataset sample. Moreover, it kept ~ 92.5% of battery power throughout interferences cancellation platform thereby it protracted the life of the sensory network.