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Adaptive cleaning for RFID data streams

Shawn R. Jeffery, Garofalakis Minos, Franklin Michael J.

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Year 2006
Type of Item Conference Full Paper
Bibliographic Citation S. R. Jeffery, M. Garofalakis and M. J. Franklin, "Adaptive cleaning for RFID data streams", in 32nd International Conference on Very Large Data Bases, 2006, pp 163-174.
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To compensate for the inherent unreliability of RFID data streams,most RFID middleware systems employ a “smoothing filter”, asliding-window aggregate that interpolates for lost readings. In thispaper, we propose SMURF, the first declarative, adaptive smoothingfilter for RFID data cleaning. SMURF models the unreliabilityof RFID readings by viewing RFID streams as a statistical sampleof tags in the physical world, and exploits techniques grounded insampling theory to drive its cleaning processes. Through the use oftools such as binomial sampling and π-estimators, SMURF continuouslyadapts the smoothing window size in a principled manner toprovide accurate RFID data to applications.