Name
Abstract | ||
|---|---|---|
Radio Frequency Identification (RFID) technology has been proliferating in recent years, especially with its wide usage in retail, warehouse and supply chain management. One of its most popular applications is to automatically detect missing products (attached with RFID tags) in a large storage place. However, most existing protocols assume that the IDs of all tags within a reader's coverage are known, while ignoring practical scenarios where the IDs of some tags may be unknown. The existence of these unknown tags will introduce false positives in those protocols, degrading their performance. Some prior art studies this problem, but their time efficiency is low, especially when the number of unknown tags is large. In this paper, we propose a missing tag detection protocol based on compressed filters, which not only reduces the filter size for better time-efficiency but also helps dampen the interference of unknown tags for high missing-tag detection accuracy. To further improve the performance, we propose a new way for tags to report their presence, greatly reducing collisions and thus improving the detection probability. Extensive simulations demonstrate that our compressed filter and collision-reduction method reduce the protocol execution time by 83% to 92% under the same missing-tag detection probability, when comparing with the best prior work. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/SAHCN.2018.8397133 | 2018 15th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON) |
Keywords | Field | DocType |
Radio Frequency Identification technology,supply chain management,RFID tags,missing tag detection protocol,missing-tag detection accuracy,missing-tag detection probability | Data mining,Computer science,Supply chain,Execution time,Interference (wave propagation),Probabilistic logic,Radio-frequency identification,Distributed computing,False positive paradox | Conference |
ISSN | ISBN | Citations |
2473-0440 | 978-1-5386-4282-5 | 2 |
PageRank | References | Authors |
0.38 | 21 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Youlin Zhang | 1 | 10 | 5.26 |
| Shiping Chen | 2 | 190 | 25.84 |
| You Zhou | 3 | 2 | 1.06 |
| Olufemi Odegbile | 4 | 2 | 0.38 |