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Challenges for Event Queries over Markovian Streams
November/December 2008 (vol. 12 no. 6)
pp. 30-36
Julie Letchner, University of Washington
Christopher Ré, University of Washington
Magdalena Balazinska, University of Washington
Matthai Philipose, Intel Research
Building applications on top of sensor data streams is challenging because sensor data is noisy. A model-based view can reduce noise by transforming raw sensor streams into streams of probabilistic state estimates, which smooth out errors and gaps. The authors propose a novel model-based view, the Markovian stream, to represent correlated probabilistic sequences. Applications interested in evaluating event queries — extracting sophisticated state sequences — can improve robustness by querying a Markovian stream view instead of querying raw data directly. The primary challenge is to properly handle the Markovian stream's correlations.

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Index Terms:
uncertainty, streams, correlations, RFID, data stream management, Markovian Stream
Citation:
Julie Letchner, Christopher Ré, Magdalena Balazinska, Matthai Philipose, "Challenges for Event Queries over Markovian Streams," IEEE Internet Computing, vol. 12, no. 6, pp. 30-36, Nov.-Dec. 2008, doi:10.1109/MIC.2008.118
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