An Efficient Early-breaking-estimation and Tree-splitting Missing RFID Tag Identification Protocol

Author:

Fan Mingqiu1ORCID,Zhang Lijuan1ORCID,Lei Lei1,Yu Chunni1

Affiliation:

1. College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China

Abstract

Retailers grapple with inventory losses primarily due to missing items, prompting the need for efficient missing tag identification methods in large-scale RFID systems. Among them, few works considered the effect of unexpected unknown tags on the missing tag identification process. With the presence of unknown tags, some missing tags may be falsely identified as present. Thus, the system’s reliability is hardly guaranteed. To resolve these challenges, we propose an efficient early-breaking-estimation and tree-splitting-based missing tag identification (ETMTI) protocol for large-scale RFID systems. ETMTI employs innovative early-breaking-estimation and deactivation methods to swiftly handle unknown tags. Subsequently, a tree-splitting-based missing tag identification method is proposed, employing a B-ary splitting tree, to rapidly identify missing tags. Additionally, a bit-tracking response strategy is implemented to reduce processing time. Theoretical analysis is conducted to determine optimal parameters for ETMTI. Simulation results illustrate that our proposed ETMTI protocol significantly outperforms benchmark methods, offering a shorter processing time and a lower false negative rate.

Funder

National Natural Science Foundation of China

Future Network Scientific Research Fund Project

National Key Research and Development Program of China

Key Research and Development Plan of Jiangsu Province

Natural Science Foundation of Jiangsu Province of China

China Postdoctoral Science Foundation

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry

Reference39 articles.

1. Verifiable Smart Packaging with Passive RFID;Wang;IEEE Trans. Mob. Comput.,2019

2. Query Diversity Schemes for Backscatter RFID Communications with Single-Antenna Tags;He;IEEE Trans. Veh. Technol.,2017

3. Song, X., Hua, Y., Yang, Y., Xing, G., Liu, F., Xu, L., and Song, T. (2023). Distributed Resource Allocation With Federated Learning for Delay-Sensitive IoV Services. IEEE Trans. Veh. Technol., 1–11.

4. National Retail Federation (2022, September 14). National Retail Security Survey 2022. [EB/OL]. Available online: https://nrf.com/research/national-retail-security-survey-2022.

5. Fast and Reliable Detection and Identification of Missing RFID Tags in the Wild;Shahzad;IEEE/ACM Trans. Netw.,2016

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