Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/67425
Title: Fast tracking the population of key tags in large-scale anonymous RFID systems
Authors: Liu, XL
Xie, X
Li, KQ
Xiao, B 
Wu, J
Qi, H
Lu, DW
Keywords: Key RFID tags
Cardinality estimation
Population tracking
Time-efficiency
Issue Date: 2017
Publisher: Institute of Electrical and Electronics Engineers
Source: IEEE/ACM transactions on networking, 2017, v. 25, no. 1, p. 278-291 How to cite?
Journal: IEEE/ACM transactions on networking 
Abstract: In large-scale radio frequency identification (RFID)enabled applications, we sometimes only pay attention to a small set of key tags, instead of all. This paper studies the problem of key tag population tracking, which aims at estimating how many key tags in a given set exist in the current RFID system and how many of them are absent. Previous work is slow to solve this problem due to the serious interference replies from a large number of ordinary (i.e., non-key) tags. However, time-efficiency is a crucial metric to the studied key tag tracking problem. In this paper, we propose a singleton slot-based estimator, which is time-efficient, because the RFID reader only needs to observe the status change of expected singleton slots corresponding to key tags instead of the whole time frame. In practice, the ratio of key tags to all current tags is small, because key members are usually rare. As a result, even when the whole time frame is long, the number of expected singleton slots is limited and the running of our protocol is very fast. To obtain good scalability in large-scale RFID systems, we exploit the sampling idea in the estimation process. A rigorous theoretical analysis shows that the proposed protocol can provide guaranteed estimation accuracy to end users. Extensive simulation results demonstrate that our scheme outperforms the prior protocols by significantly reducing the time cost.
URI: http://hdl.handle.net/10397/67425
ISSN: 1063-6692
DOI: 10.1109/TNET.2016.2576904
Appears in Collections:Journal/Magazine Article

Access
View full-text via PolyU eLinks SFX Query
Show full item record

SCOPUSTM   
Citations

2
Last Week
0
Last month
Citations as of Oct 15, 2017

WEB OF SCIENCETM
Citations

1
Last Week
0
Last month
Citations as of Oct 15, 2017

Page view(s)

76
Last Week
0
Last month
Checked on Oct 15, 2017

Google ScholarTM

Check

Altmetric



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.