Efficient protocol design for dynamic tag population monitoring in large-scale radio frequency identification systems

Qingjun Xiao, Kai Bu, Bin Xiao, Limin Sun

Research output: Journal article publicationJournal articleAcademic researchpeer-review

4 Citations (Scopus)


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.
Original languageEnglish
Pages (from-to)2080-2097
Number of pages18
JournalConcurrency Computation Practice and Experience
Issue number14
Publication statusPublished - 25 Sept 2013


  • dynamic tag population
  • RFID
  • tag population monitoring
  • ubiquitous computing

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Computer Science Applications
  • Computer Networks and Communications
  • Computational Theory and Mathematics


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