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    A fast approach to unknown tag identification in large scale RFID systems

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    Publication date
    2013
    Author
    Liu, X.
    Li, K.
    Shen, Y.
    Min, Geyong
    Xiao, B.
    Qu, W.
    Li, H.
    Keyword
    Protocols; Vectors; RFID tags; Accuracy; Filtering; Educational institutions
    Peer-Reviewed
    Yes
    
    Metadata
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    Abstract
    Radio Frequency Identification (RFID) technology has been widely applied in many scenarios such as inventory control, supply chain management due to its superior properties including fast identification and relatively long interrogating range over barcode systems. It is critical to efficiently identify the unknown tags because these tags can appear when new tagged objects are moved in or wrongly placed. The state-of-the-art Basic Unknown tag Identification Protocol-with Collision-Fresh slot paring (BUIP-CF) protocol can first deactivate all the known tags and then collect all the unknown tags. However, BUIP-CF protocol investigates an ALOHA-like technique and causes too many tag responses, which results in low efficiency. This paper proposes a Fast Unknown tag Identification (FUI) protocol which investigates an indicator vector to label the unknown tags with a given accuracy and removes the time-consuming tag responses in the deactivation phase. FUI also adopts the classical Enhanced Dynamic Framed Slotted ALOHA (EDFSA) protocol to collect the labeled unknown tags. We then investigate the optimal parameter settings to maximize the performance of the proposed FUI protocol. Extensive simulation experiments are conducted to evaluate the performance of the proposed FUI protocol and the experimental results show that it considerably outperforms the state-of-the-art protocol.
    URI
    http://hdl.handle.net/10454/9682
    Version
    No full-text available in the repository
    Citation
    Liu X, Li K, Shen Y, Min G et al (2013) A fast approach to unknown tag identification in large scale RFID systems. In: 2013 22nd International Conference on Computer Communications and Networks (ICCCN). 30 Jul-2 Aug 2013. Nassau, The Bahamas: . IEEE: 1-7.
    Type
    Conference Paper
    Collections
    Engineering and Informatics Publications

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