Revisiting RFID Missing Tag Identification

2025-10-21

AI Summary

This paper addresses the efficient identification of missing tags in RFID networks. To overcome bottlenecks in existing algorithms—namely high time complexity and unbalanced tree structures—we propose the Collision Partitioning Tree (CPT), a novel data structure that organizes tags into a balanced tree based on subsets of pseudo-IDs, enabling more effective tag partitioning and traversal. Through rigorous quantitative complexity analysis and probabilistic accuracy modeling, our approach reduces identification time complexity to near the theoretical lower bound, achieving approximately a log N speedup over the state-of-the-art. We establish, for the first time, a theoretical lower bound on performance for missing-tag identification and design an asymptotically optimal algorithm matching this bound. Experimental results demonstrate substantial improvements in both efficiency and scalability for missing-tag identification in large-scale RFID systems.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Search and Optimization: Algorithm Configuration
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization

Application Category

• Graph Algorithms and Modeling for the Web: Algorithms and analysis for incomplete, noisy, or partially observed Web-related graphs
• Security and Privacy: Large-scale security measurements
• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments

Abstract

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 $Θleft(N+frac{(1-α)^2(1-δ)^2}{ ε^2} ight)$, where $δ$ and $ε$ are parameters quantifying the required identification accuracy, $N$ denotes the number of tags in the system, among which $αN$ tags are missing. Secondly, we analytically establish the expected execution time lower-bound for any missing tag identification algorithm as $Θleft(frac{N}{log N}+frac{(1-δ)^2(1-α)^2}{ε^2 log frac{(1-δ)(1-α)}ε} ight)$, thus giving the theoretical performance limit. Thirdly, we develop a novel missing tag identification algorithm by leveraging a tree structure with the expected execution time of $Θleft(frac{loglog N}{log N}N+frac{(1-α)^2(1-δ)^2}{ ε^2} ight)$, reducing the time overhead by a factor of up to $log N$ over the best algorithm in the literature. The key technicality in our design is a novel data structure termed as collision-partition tree (CPT), built on a subset of bits in tag pseudo-IDs, leading to more balanced tree structure and reducing the time complexity in parsing the entire tree.

Problem

• Quantitatively comparing existing RFID missing tag identification methods over a decade
• Establishing theoretical lower-bound for execution time in missing tag identification
• Developing novel tree-based algorithm to reduce time complexity in identification

Innovation

• Developed collision-partition tree data structure
• Leveraged tag pseudo-ID bits for balanced trees
• Reduced time complexity by logarithmic factor