URI | http://purl.tuc.gr/dl/dias/CC96CE04-CBF2-4254-99E9-60E54877435C | - |
Αναγνωριστικό | http://www.vldb.org/conf/2006/p163-jeffery.pdf | - |
Γλώσσα | en | - |
Μέγεθος | 12 pages | en |
Τίτλος | Adaptive cleaning for RFID data streams | en |
Δημιουργός | Shawn R. Jeffery | en |
Δημιουργός | Garofalakis Minos | en |
Δημιουργός | Γαροφαλακης Μινως | el |
Δημιουργός | Franklin Michael J. | en |
Εκδότης | Association for Computing Machinery | en |
Περίληψη | To compensate for the inherent unreliability of RFID data streams,
most RFID middleware systems employ a “smoothing filter”, a
sliding-window aggregate that interpolates for lost readings. In this
paper, we propose SMURF, the first declarative, adaptive smoothing
filter for RFID data cleaning. SMURF models the unreliability
of RFID readings by viewing RFID streams as a statistical sample
of tags in the physical world, and exploits techniques grounded in
sampling theory to drive its cleaning processes. Through the use of
tools such as binomial sampling and π-estimators, SMURF continuously
adapts the smoothing window size in a principled manner to
provide accurate RFID data to applications. | en |
Τύπος | Πλήρης Δημοσίευση σε Συνέδριο | el |
Τύπος | Conference Full Paper | en |
Άδεια Χρήσης | http://creativecommons.org/licenses/by/4.0/ | en |
Ημερομηνία | 2015-12-01 | - |
Ημερομηνία Δημοσίευσης | 2006 | - |
Θεματική Κατηγορία | Databases technology | en |
Βιβλιογραφική Αναφορά | 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.
| en |