dc.contributor.authorZheng, Yuanqing.
dc.contributor.authorLi, Mo.
dc.date.accessioned2013-10-14T03:17:17Z
dc.date.available2013-10-14T03:17:17Z
dc.date.copyright2012en_US
dc.date.issued2012
dc.identifier.citationZheng, Y., & Li, M. (2012). PET: Probabilistic Estimating Tree for large-scale RFID estimation. IEEE transactions on mobile computing, 11(11), 1763-1774.
dc.identifier.urihttp://hdl.handle.net/10220/16466
dc.description.abstractEstimating the number of RFID tags in the region of interest is an important task in many RFID applications. In this paper, we propose a novel approach for efficiently estimating the approximate number of RFID tags. Compared with existing approaches, the proposed Probabilistic Estimating Tree (PET) protocol achieves O(loglogn) estimation efficiency, which remarkably reduces the estimation time while meeting the accuracy requirement. PET also largely reduces the computation and memory overhead at RFID tags. As a result, we are able to apply PET with passive RFID tags and provide scalable and inexpensive solutions for large-scale RFID systems. We validate the efficacy and effectiveness of PET through theoretical analysis as well as extensive simulations. Our results suggest that PET outperforms existing approaches in terms of estimation accuracy, efficiency, and overhead.en_US
dc.language.isoenen_US
dc.relation.ispartofseriesIEEE transactions on mobile computingen_US
dc.subjectDRNTU::Engineering::Computer science and engineering
dc.titlePET : Probabilistic Estimating Tree for large-scale RFID estimationen_US
dc.typeJournal Article
dc.contributor.schoolSchool of Computer Engineeringen_US
dc.identifier.doihttp://dx.doi.org/10.1109/TMC.2011.238


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