A shorter version of the paper was presented at the 9th IEEE/IFIP International Conference on Embedded and Ubiquitous Computing, 2011.
Special Issue Paper
Efficient protocol design for dynamic tag population monitoring in large-scale radio frequency identification systems†
Article first published online: 28 MAR 2012
Copyright © 2012 John Wiley & Sons, Ltd.
Concurrency and Computation: Practice and Experience
Special Issue: Advances in parallel, distributed, embedded and ubiquitous systems (ICA3PP 2011)
Volume 25, Issue 14, pages 2080–2097, 25 September 2013
How to Cite
Xiao, Q., Bu, K., Xiao, B. and Sun, L. (2013), Efficient protocol design for dynamic tag population monitoring in large-scale radio frequency identification systems. Concurrency Computat.: Pract. Exper., 25: 2080–2097. doi: 10.1002/cpe.2835
- Issue published online: 12 SEP 2013
- Article first published online: 28 MAR 2012
- Manuscript Accepted: 22 FEB 2012
- Manuscript Revised: 21 FEB 2012
- Manuscript Received: 21 DEC 2011
- ubiquitous computing;
- dynamic tag population;
- tag population monitoring
As radio frequency identification (RFID) tags become more ubiquitously available, they will stay in dynamic environments where tags can freely enter or leave RFID readers' interrogation range. With such a dynamic tag population, there arises a problem of population monitoring, whose purpose is to identify the missing tags that have departed from the reading range and the new tags that have newly entered. This problem is a new problem which cannot be well solved by the conventional tag identification protocols. In this paper, we first show that this traditional approach is inefficient, because it collects all the tag IDs in each scan and ignores the ready-for-use knowledge of the tag population in a previous scan. To be more efficient, we present three protocols: (i) a baseline protocol that improves the traditional tag identification protocol by optimizing its length of random number used for collision detection; (ii) a novel one-phase protocol with easy labor to identify exactly the new tags and the missing tags by fully utilizing the knowledge of previous tag population; and (iii) a hybrid protocol that smartly combines the baseline protocol and the one-phase protocol. Its purpose is to deal with the situation that the knowledge of previous tag population is highly inconsistent with the current tag population. This hybrid protocol, as shown by our analysis, can improve the tag monitoring accuracy by 25%, and improve the time efficiency by 55.3%, as compared with a recent work (called two-phase protocol), which also identifies the population changes. Copyright © 2012 John Wiley & Sons, Ltd.