High efficient tag identification protocols for large-scale RFID systems

Zhang, Lijuan (2017) High efficient tag identification protocols for large-scale RFID systems. PhD thesis, James Cook University.

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As one of the most important auto-identification technologies, radio frequency identification (RFID) is the most basic technology used to connect physical objects in support of intelligent decision-making in Internet-of-Things (IoT) networks. Building up the connections between physical objects and virtual networks, RFID systems have been in widespread use in numerous large-scale applications, such as logistics, management and inventory tracking. Since the reader and tags share the same wireless channel in such systems, tag collision occurs when multiple tags reply to the reader simultaneously, which not only increases the identification delay but also wastes bandwidth. In this thesis, three efficient tag identification protocols are proposed to reduce the collisions in three typical application scenarios, i.e., missing tag identification, moving tag recognition and energy-saving of passive systems with a portable reader.

Firstly, with RFID systems being used more and more widely in warehouses and logistics applications, effectively and efficiently identifying missing tags be- comes one of the most fundamental tasks, especially for asset management and anti-theft purposes. To identify missing tags, we propose a time-efficient pair-wise collision-resolving missing-tag identification (PCMTI) protocol through designing novel pair-reply and two-collision slot resolving strategies. Compared with previous work, PCMTI can verify two tags in one short response slot simultaneously and identify the tags in all the two-tag collision slots, resulting in less identification time than previous works.

Secondly, in mobile systems with moving tags, many tags move in and out of the system continuously, resulting in limited time for the reader to identify the tags within its reading range. To improve the identification time and reduce the tag-lost ratio of mobile systems, an efficient bit-detecting (EBD) protocol is proposed. With a new bit monitoring strategy and an M-ary bit-detecting tree recognition method proposed, EBD can effectively verify the known tags using a few number of slots and rapidly identify unknown tags without generating any idle slots. EBD shows better time performance and lower tag-lost ratio than existing protocols reported in the literature.

Thirdly, in passive systems with a portable reader, the energy cost of the reader is caused not only by its own communication operations but also by powering all the tags around it. To prolong the reader's battery life, an M-ary collision tree (MCT) protocol is proposed for time- and energy-saving of the tag identification process. Using the positions of colliding bits, MCT can identify all the tags with fewer collision slots and transmitted message bits, which greatly reduces the time and energy costs.

Through solving the tag identification problem in various applications, this thesis is of great significance and practical use for wider implementation of large-scale RFID systems.

Item ID: 53101
Item Type: Thesis (PhD)
Keywords: missing tag detecting, radio frequency identification, RFID, tag anti-collision protocol, tag identification, tag monitoring, tag recognition
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Publications arising from this thesis are available from the Related URLs field. The publications are:

Chapter 3: Zhang, Lijuan, Xiang, Wei, Atkinson, Ian, and Tang, Xiaohu (2017) A time-efficient pair-wise collision-resolving protocol for missing tag identification. IEEE Transactions on Communications, 65 (12). pp. 5348-5361.

Chapter 4: Zhang, Lijuan, Xiang, Wei, and Tan, Xiaohu (2018) An efficient bit-detecting protocol for continuous tag recognition in mobile RFID systems. IEEE Transactions on Mobile Computing, 17 (3). pp. 503-516.

Date Deposited: 11 Apr 2018 03:04
FoR Codes: 09 ENGINEERING > 0906 Electrical and Electronic Engineering > 090699 Electrical and Electronic Engineering not elsewhere classified @ 50%
10 TECHNOLOGY > 1005 Communications Technologies > 100504 Data Communications @ 50%
SEO Codes: 89 INFORMATION AND COMMUNICATION SERVICES > 8901 Communication Networks and Services > 890199 Communication Networks and Services not elsewhere classified @ 100%
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