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Challenges for Event Queries over Markovian Streams

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4 Author(s)
Letchner, J. ; Washington Univ., Washington, DC ; Re, C. ; Balazinska, M. ; Philipose, M.

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.

Published in:

Internet Computing, IEEE  (Volume:12 ,  Issue: 6 )