Comparative study of RLE & K-RLE compression and decompression in WSN

Abstract

Wireless sensor network is very active research area. WSNs are very popular nowadays due to their wide range of application areas like in health monitoring, industrial monitoring, environmental monitoring, inventory location monitoring, surveillance, factory and process automation, object tracking, precision agriculture, disaster management, and equipment diagnostics etc. To perform a specific task sensor nodes in WSNs communicate with each other wirelessly and they are generally self-organized. Each node is equipped with sensors, battery, processor, wireless transceiver, and memory. Due to the limited capacity of the batteries, it is important to consider the energy (power) in the design and deployment of wireless sensor networks (WSNs). Energy is consumed during sensing, processing and communication. But the major power consumer is the communication unit in WSNs, one of possible solution that can help to reduce the amount of data transmitted between wireless sensor nodes resulting in power saving is the use of efficient data compression technique. In this paper we evaluate a K-RLE method which is inspired from existing Run Length Encoding algorithm. Method is designed in Matlab software. With creating effective GUI, we show here the compression ratios for different values of K with variable input temperature dataset values. We get higher compression ratios for long length of runs. It is found that as the values of K goes on increasing, the compression ratios are very high. K-RLE is efficient but lossy technique.