Capturing Sensor-Generated Time Series with Quality Guarantees
CALIFORNIA UNIV IRVINE
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We are interested in capturing time series generated by small wireless electronic sensors. Battery-operated sensors must avoid heavy use of their wireless radio which is a key cause of energy dissipation. When many sensors transmit, the resources of the recipient of the data are taxed hence, limiting communication will benefit the recipient as well. In our paper we show how time series generated by sensors can be captured and stored in a database system archive. Sensors compress time series instead of sending them in raw form. We propose an optimal on-line algorithm for constructing a piecewise constant approximation PCA of a time series which guarantees that the compressed representation satisfies an error bound on the Linfinity distance. in addition to the capture task, we often want to estimate the values of a time series ahead of time, e.g., to answer real-time queries. To achieve this, sensors may fit predictive models on observed data, sending parameters of these models to the archive. We exploit the interplay between prediction and compression in a unified framework that avoids duplicating effort and leads to reduced communication.
- Numerical Mathematics
- Miscellaneous Detection and Detectors