A new efficient energy implementation of K-RLE algorithm for WSN

Energy consumption is a critical issue affecting the lifetime of WSN. It is observed that energy consumed for processing the data to transmit is considerably less than used in transmission. A number of techniques are proposed to solve this problem. Data compression is a promising approach to reduce transmitted data and inter-nodes communications over wireless channels. In this paper, we present a new approach to implement the K-RLE algorithm in WSN giving a trade-off between energy consumption and compression rate efficiency. Our solution called C-RLE is validated and qualified on a Cortex-M3 based WSN node and compared to the previous implementations of K-RLE. Experimental results show that proposed implementation preserves the performance of the K-RLE in terms of compression ratio. Moreover, it significantly performs better than the existing implementations of K-RLE in terms of energy consumption with a gain of 30.41%.