Compression of Wireless Sensor Node Data for Transmission based on Minimalist, Adaptive, and Streaming Compression Algorithm

A wireless sensor network (WSN) typically contains various sensor nodes which are spread across a geographical area for data collection like temperature, pressure, humidity, wind speed, rain fall, and soil moisture. Sensor nodes in the wireless sensor networks, are usually constrained in resources, such as having limited amount of power, memory storage and communication capability. In order to conserve the power consumption of the sensor node, data compression will be implemented through application of algorithms such as Minimalist, Adaptive, and Streaming (MAS) Compression Algorithm and Sensor-Lempel Ziv Welch (S-LZW). Using these compression techniques, its effects on the power consumption of the sensor node was observed. Upon using statistical methods, when comparing the power consumption during transmission between uncompressed and MAS compressed data, a P-value of 0.001 was computed which is less than 0.05, which has a 95% confidence level. MAS compression algorithm was able to reduce power consumption during transmission, between 53.55439% and 55.95118% which signifies that the power consumption during transmission was reduced when applying data compression algorithms.