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Issue No. 06 - November/December (2008 vol. 12)
ISSN: 1089-7801
pp: 30-36
Magdalena Balazinska , University of Washington
Matthai Philipose , Intel Research
Christopher Ré , University of Washington
Julie Letchner , University of Washington
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.
uncertainty, streams, correlations, RFID, data stream management, Markovian Stream
Magdalena Balazinska, Matthai Philipose, Christopher Ré, Julie Letchner, "Challenges for Event Queries over Markovian Streams", IEEE Internet Computing, vol. 12, no. , pp. 30-36, November/December 2008, doi:10.1109/MIC.2008.118
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