Energy-Efficient Data Acquisition By Adaptive Sampling for Wireless Sensor Networks

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Law, Yee Wei and Chatterjea, Supriyo and Jin, Jiong and Hanselmann, Thomas and Palaniswami, Marimuthu (2008) Energy-Efficient Data Acquisition By Adaptive Sampling for Wireless Sensor Networks. [Report]

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Abstract:Wireless sensor networks (WSNs) are well suited for environment monitoring. However, some highly specialized sensors (e.g. hydrological sensors) have high power demand, and without due care, they can exhaust the battery supply
quickly. Taking measurements with this kind of sensors can also overwhelm the communication resources by far. One way to reduce the power drawn by these high-demand sensors is adaptive sampling, i.e., to skip sampling when data loss is estimated to be low. Here, we present an adaptive sampling algorithm based on the Box-Jenkins approach in time series analysis. To measure the performance of our algorithms, we use the ratio of the reduction factor to root mean square error (RMSE). The rationale of the metric is that the best algorithm is the algorithm that gives the most reduction in the amount of sampling and yet the the smallest RMSE. For the datasets used in our simulations, our algorithm is capable of reducing the amount of sampling by 24% to 49%. For seven out of eight datasets, our algorithm performs better than the best in the literature so far in terms of the reduction/RMSE ratio.
Item Type:Report
Copyright:© 2008 University of Twente, Centre for Telematics and Information Technology
Faculty:
Electrical Engineering, Mathematics and Computer Science (EEMCS)
Research Group:
Link to this item:http://purl.utwente.nl/publications/65359
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Metis ID: 255877