Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/102619
Title: PET : Probabilistic Estimating Tree for large-scale RFID estimation
Authors: Li, Mo.
Zheng, Yuanqing.
Keywords: DRNTU::Engineering::Computer science and engineering
Issue Date: 2012
Source: Zheng, Y., & Li, M. (2012). PET: Probabilistic Estimating Tree for large-scale RFID estimation. IEEE transactions on mobile computing, 11(11), 1763-1774.
Series/Report no.: IEEE transactions on mobile computing
Abstract: Estimating 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.
URI: https://hdl.handle.net/10356/102619
http://hdl.handle.net/10220/16466
DOI: 10.1109/TMC.2011.238
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:SCSE Journal Articles

SCOPUSTM   
Citations 5

55
Updated on Jan 26, 2023

Web of ScienceTM
Citations 10

46
Updated on Jan 23, 2023

Page view(s) 20

567
Updated on Feb 5, 2023

Google ScholarTM

Check

Altmetric


Plumx

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.