Novel distributed wavelet transforms and routing algorithms for efficient data gathering in sensor webs
Godwin Shen, Yeonho Lee, Sung-Won Lee, Sundeep Pattem, Aaron Tu, Bhaskar Krishnamachari, Antonio J. Ortega, Michael Cheng, Sam Dolinar, Aaron B. Kiely, Matt Klimesh, Hua Xie · 2008
In this work we present our ongoing investigation of novel ap-proaches for information processing and representation in a sensor web. Since sensor nodes capture spatially and temporally corre-lated information there are several alternatives in order to exploit correlation, namely, (a) sensors can exploit this spatial correlation by first exchanging data and then compressing it in a distributed manner, or (b) sensors can exploit temporal correlation locally only, or (c) sensors can even exploit correlation across time and space. We aim to develop techniques based on the last approach, which will tend to reduce the total amount of data to be trans-ferred in the sensor web at the expense of some additional (po-tentially minor) power consumption. We are investigating meth-ods for sampling, routing, processing and compression. All of these aim at maximizing the quality of the data available at the