Receive Only Necessary: Efficient Tag Category Identification in Large-scale RFID Systems

Xuan Liu, Jiangjin Yin, Shigeng Zhang, Kenli Li, Song Guo

Research output: Journal article publicationJournal articleAcademic researchpeer-review

10 Citations (Scopus)

Abstract

RFID systems have been widely deployed for various applications such as inventory control, retail management, and object tracking. In many scenarios, coarse-grained system management of tag categories is more common than traditional system management of individual tags. Existing works require knowing category IDs in advance, however, few protocols have been specially designed to obtain category IDs in multi-category RFID systems. In this paper, we propose CIP, a time-efficient protocol specially designed to collect category IDs in multi-category RFID systems. The challenge is to avoid repeatedly collecting category IDs from multiple tags belonging to the same category. We address this challenge by squeezing tags in the same category into the same time slot and letting them reply to the reader simultaneously. Considering the reader may receive signals from different tags in a slot, we exploit the Manchester coding to decode the aggregated signals. CIP collects each category ID only once and achieves high time-efficiency by avoiding redundant identification of the same category ID. We further enhance CIP by utilizing the lightweight vectors to specify the order of tags' replying and avoid useless slots. Experimental results show that our protocols can significantly improve time efficiency by 67% when compared with the state-of-the-art.

Original languageEnglish
Pages (from-to)1157-1169
JournalIEEE Transactions on Mobile Computing
DOIs
Publication statusAccepted/In press - 2021

Keywords

  • Category Identification
  • Computer science
  • Encoding
  • Estimation
  • Manchester Coding
  • Mobile computing
  • Protocols
  • Radio Frequency Identification (RFID) Systems
  • Radiofrequency identification
  • Testing
  • Time Efficiency

ASJC Scopus subject areas

  • Software
  • Computer Networks and Communications
  • Electrical and Electronic Engineering

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