We revisit the problem of missing tag identification in RFID networks by making three contributions. Firstly, we quantitatively compare and gauge the existing propositions spanning over a decade on missing tag identification. We show that the expected execution time of the best solution in the literature is <tex-math notation="LaTeX">Θ (N+(1-α)²(1-δ)²/ ε²)</tex-math> , where <tex-math notation="LaTeX">δ</tex-math> and <tex-math notation="LaTeX">ε</tex-math> are parameters quantifying the required identification accuracy, <tex-math notation="LaTeX">N</tex-math> denotes the number of tags in the system, among which <tex-math notation="LaTeX">α N</tex-math> tags are missing. Secondly, we analytically establish the expected execution time lower-bound for any missing tag identification algorithm as <tex-math notation="LaTeX">Θ(N/log N+(1-δ)²(1-α)²ε² log (1-δ)(1-α)/ε)</tex-math> , thus setting the theoretical performance limit. Thirdly, we develop two novel missing tag identification algorithms with the expected execution time of <tex-math notation="LaTeX">Θ (loglog N/log NN+(1-α)²(1-δ)²/ ε²)</tex-math> , reducing the time overhead by a factor of up to <tex-math notation="LaTeX">log N</tex-math> over the best algorithm in the literature. The key technicality in our first algorithm is a novel data structure termed as collision-partition tree (CPT), built on a subset of bits in tag pseudo-IDs, leading to a more balanced tree structure and reducing the time complexity in parsing the entire tree. To further improve time efficiency, our second algorithm integrates multiple CPTs to form a collision-partition forest (CPF), reducing both the number of slots and the quantity of information broadcasting.
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Liu et al. (2024) studied this question.
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