PET: Probabilistic estimating tree for large-scale RFID estimation

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52 Citations (Scopus)

Abstract

Estimating the number of RFID tags in the region of interest is an important task in many RFID applications. In this paper, we propose a novel approach for efficiently estimating the approximate number of RFID tags. Compared with existing approaches, the proposed Probabilistic Estimating Tree (PET) protocol achieves O(log log n) estimation efficiency, which remarkably reduces the estimation time while meeting the accuracy requirement. PET also largely reduces the computation and memory overhead at RFID tags. As a result, we are able to apply PET with passive RFID tags and provide scalable and inexpensive solutions for large-scale RFID systems. We validate the efficacy and effectiveness of PET through theoretical analysis as well as extensive simulations. Our results suggest that PET outperforms existing approaches in terms of estimation accuracy, efficiency, and overhead.
Original languageEnglish
Article number6072210
Pages (from-to)1763-1774
Number of pages12
JournalIEEE Transactions on Mobile Computing
Volume11
Issue number11
DOIs
Publication statusPublished - 1 Oct 2012
Externally publishedYes

Keywords

  • aloha networks
  • RFID systems
  • tag estimation

ASJC Scopus subject areas

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

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