Static Algorithmic Transformation Based Low Power Wireless Sensor Networks

Wireless Sensor Networks (WSN) has become a very significant enabling technology in civil, military, radio communication and medical applications for collecting and processing of complex environmental data. Wireless sensor networks have several important attributes that require special attention to device design. These include the need for inexpensive, long-lasting, highly reliable devices coupled with very low performance requirements. Radio communication has highest energy consumption in wireless sensor nodes. Sensor nodes are battery driven and have limited power. Hence, sensor nodes lifetime on the order of months to years. Hence, energy consumption is the important factor in determining sensor nodes lifetime. Power consumption is high during data processing and data transmission process. Inorder to reduce number of data sensed by nodes Data Aggregation is used. Data Aggregation converts multiple sensed data into single data. Here proposing, data aggregation process implemented using DVFS (Dynamic Voltage and Frequency Scaling) algorithm used at input side along with Static Algorithmic Transformation (SAT) uses folded tree architecture to reduce power by reducing number of processing elements and to improve performance of sensor nodes. Experimental results shows that using DVFS algorithm reduces power up to 13% compared to existing processing methods.