DocumentCode
2330955
Title
Energy Efficient Algorithms for the RFID Estimation Problem
Author
Li, Tao ; Wu, Samuel ; Chen, Shigang ; Yang, Mark
Author_Institution
Dept. of Comput. & Inf. Sci. & Eng., Univ. of Florida, Gainesville, FL, USA
fYear
2010
fDate
14-19 March 2010
Firstpage
1
Lastpage
9
Abstract
RFID has been gaining popularity for inventory control, object tracking, and supply chain management in warehouses, retail stores, hospitals, etc. Periodically and automatically estimating the number of RFID tags deployed in a large area has many important applications in inventory management and theft detection. The prior work focuses on designing time-efficient algorithms that can estimate tens of thousands of tags in seconds. We observe that, for a RFID reader to access tags in a large area, active tags are likely to be used. These tags are battery-powered and use their own energy for information transmission. However, recharging batteries for tens of thousands of tags is laborious. Unlike the prior work, this paper studies the RFID estimation problem from the energy angle. Our goal is to reduce the amount of energy that is consumed by the tags during the estimation procedure. We design several energy-efficient probabilistic algorithms that iteratively refine a control parameter to optimize the information carried in the transmissions from the tags, such that both the number and the size of the transmissions are minimized.
Keywords
maximum likelihood estimation; radiofrequency identification; stock control; supply chain management; RFID estimation problem; information transmission; inventory control; inventory management; maximum likelihood estimation; object tracking; radiofrequency identification; supply chain management; theft detection; Algorithm design and analysis; Batteries; Energy efficiency; Hospitals; Inventory control; Inventory management; Iterative algorithms; RFID tags; Radiofrequency identification; Supply chain management;
fLanguage
English
Publisher
ieee
Conference_Titel
INFOCOM, 2010 Proceedings IEEE
Conference_Location
San Diego, CA
ISSN
0743-166X
Print_ISBN
978-1-4244-5836-3
Type
conf
DOI
10.1109/INFCOM.2010.5461947
Filename
5461947
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