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Identifying the Missing Tags in Categorized RFID Systems
Author(s) -
Jumin Zhao,
Wenting Li,
Dengao Li
Publication year - 2014
Publication title -
international journal of distributed sensor networks
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.324
H-Index - 53
eISSN - 1550-1477
pISSN - 1550-1329
DOI - 10.1155/2014/582951
Subject(s) - computer science , identification (biology) , protocol (science) , frame (networking) , variety (cybernetics) , radio frequency identification , missing data , data mining , scheme (mathematics) , energy consumption , volume (thermodynamics) , state (computer science) , real time computing , database , computer network , artificial intelligence , computer security , machine learning , algorithm , medicine , mathematical analysis , ecology , botany , alternative medicine , mathematics , physics , pathology , quantum mechanics , biology
RFID is a practical technology that supports extensive applications such as warehouse management, asset tracking, and transportation and logistics. Identifying the missing tags in categorized RFID systems is of practical importance for a variety of applications but is not yet thoroughly investigated. Traditional missing tag identification approaches can not solve the problem efficiently because they do not distinguish categories, leading to long scanning time and high energy consumption. To achieve time and energy efficiency, this paper proposes three protocols. First, we formally formulate the problem of missing tag identification in categorized RFID systems. And then a compact structure is proposed to active tags in protocols which carries a large volume aggregated tag ID information. To further improve the utilization rate of a frame, we design a rehash scheme to change empty slots and collision slots into singleton slots. We evaluate the performance of our protocols with extensive simulations. Compared with the physical-layer missing tag identification protocol (P-MTI), which is the state-of-the-art missing tag identification technology, our best protocol reduces the execution time up to 99.8%.

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