Reliable data approximation in wireless sensor network

Wireless Sensor Network (WSN) is highly budgeted by energy since sensor nodes are mostly battery-powered and deployed in hard-to-reach area for prolonged duration. Moreover radio communication is very expensive for WSN. At the same time, a substantial portion WSN applications require periodic data collection. In this paper we investigate this issue in depth and present a solution architecture: 2PDA, that eliminates repeated transmission. The solution is founded upon temporal linear correlation among sensor data. Instead of sending each data packet we model them using method of least square that exploits temporal correlation among sensor data. 2PDA observes sensor data and performs operation parameterized by application-precision. After successful computation only the parameters of the model are sent over the radio to the application-end or sink. 2PDA was implemented in TinyOS. Implementation showed a significant improvement (i.e. 80%) for the node’s life-time. Rigorous numerical analysis was done on various sensor data which indicated its modest efficiency under different scenario. Effects of various parameters such as type of sensory information, time and place of data collection were assessed. Finally a network simulation was carried out to evaluate its scalability.