Wireless Sensor Network (WSN) consists of spatially distributed self-organizing, low-powered sensing devices with limited computational and communication resources to cooperatively monitor conditions, such as temperature, sound, vibration, pressure and humidity over a specific area for some specific purposes like target tracking, area monitoring, industrial monitoring, health monitoring, surveillance, environmental monitoring etc and report the collected data of all sensors to the user for analysis. Energy is a primary constraint in the design of sensor networks. This fundamental energy constraint further limits everything from data sensing rates and link bandwidth, to node size and weight. In most cases, the radio is the main energy consumer of the system; lifetime of sensor node may extended by reducing transmissions/receptions of data. It is useful to apply data compression to reduce the volume of data, and the associated energy consumption of transmission. In this paper, we propose a simple and efficient data compression algorithm which is lossless and particularly suited to the reduced memory and computational resources of a WSN node. The proposed data compression algorithm gives good compression ratio for highly correlated data as well as low correlated data.
K. Maurya, Ashish; Singh, Dinesh; and K. Sarje, Anil
"Median Predictor based Data Compression Algorithm for Wireless Sensor Network,"
International Journal of Smart Sensor and Adhoc Network: Vol. 1
, Article 15.
Available at: https://www.interscience.in/ijssan/vol1/iss1/15