5th International ICST Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness

Research Article

Performance Improvement of Generation-2 RFID Protocol

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  • @INPROCEEDINGS{10.4108/ICST.QSHINE2008.3926,
        author={Chonggang Wang and Mahmoud Daneshmand and Bo Li and Kazem Sohraby},
        title={Performance Improvement of Generation-2 RFID Protocol},
        proceedings={5th International ICST Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness},
        publisher={ICST},
        proceedings_a={QSHINE},
        year={2010},
        month={5},
        keywords={Radio Frequency Identification Air Interface Generation-2 RFID Performance Analysis Tag Identification Speed},
        doi={10.4108/ICST.QSHINE2008.3926}
    }
    
  • Chonggang Wang
    Mahmoud Daneshmand
    Bo Li
    Kazem Sohraby
    Year: 2010
    Performance Improvement of Generation-2 RFID Protocol
    QSHINE
    ICST
    DOI: 10.4108/ICST.QSHINE2008.3926
Chonggang Wang1,*, Mahmoud Daneshmand2,*, Bo Li3,*, Kazem Sohraby1,*
  • 1: University of Arkansas Fayetteville, AR 72701 USA
  • 2: AT&T Labs Research Florham Park, NJ 07932 USA
  • 3: Hong Kong University of Science and Technology Hong Kong, China
*Contact email: cgwang@uark.edu, daneshmand@att.com, bli@cse.ust.hk, sohraby@uark.edu

Abstract

Radio frequency identification (RFID) provides a non-line-of-sight and contactless approach for object identification. But if there are multiple tags in the range of an RFID reader, tag collision can take place due to radio signal interference and therefore an anti-collision algorithm is required to resolve collisions. Recently, EPCglobal RFID generation-2 (Gen-2) protocol [1] is proposed for ultra-high frequency (UHF) passive tags and is being deployed. Gen-2 designs a slotted random anti-collision algorithm, especially, an adaptive slot-counter (Q) selection algorithm. The integer-valued parameter Q in Gen-2 plays a critical role in tag collision resolution. This adaptive algorithm dynamically adjusts the value of Q based on the type of replies from tags. In this paper, we propose an optimal Q algorithm that determines the optimal values of Q according to the number of remaining tags and in turn to optimize tag identification speed (TIS). It’s been demonstrated through extensive simulations that the proposed algorithm achieves higher TIS than Gen-2 adaptive Q algorithm.