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ID-Free multigroup cardinality estimation for massive RFID Tags in IoT

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Authors

  • Tsu Kuang Lee
  • Chih Chieh Chen
  • Yi Ren
  • Cheng Kuan Lin
  • Yu Chee Tseng

Organisational units

Abstract

The Internet of Things (IoT) has become the hottest in both the research community and industry. Among them, Radio Frequency Identification (RFID) plays a key role in IoT. On the RFID tags estimation problem, most existing researches are trying to identifying tags' ID rather than counting the number of tags. But the number of tags is useful information in many applications such as stock management and traffic flow management. Massive tags cause taking a lot of cost and time in the estimate. So an essential problem is how to quickly and accurately estimate the number of massive tags. In order to solve this problem, this paper proposes an accuracy and efficiency hybrid scheme by decreasing time and space complexity. The results of simulation conducted to test the effectiveness of the proposed approach, which matches well with the theoretical analytical model.

Details

Original languageEnglish
Title of host publicationProceedings - 2019 IEEE VTS Asia Pacific Wireless Communications Symposium, APWCS 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728112046
DOIs
Publication statusPublished - 30 Sep 2019
Event2019 IEEE VTS Asia Pacific Wireless Communications Symposium, APWCS 2019 - Singapore, Singapore
Duration: 28 Aug 201930 Aug 2019

Publication series

NameProceedings - 2019 IEEE VTS Asia Pacific Wireless Communications Symposium, APWCS 2019

Conference

Conference2019 IEEE VTS Asia Pacific Wireless Communications Symposium, APWCS 2019
CountrySingapore
CitySingapore
Period28/08/1930/08/19

Keywords

    Research areas

  • Hint, Internet of Thinks (IoT), RFID, Tags

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ID: 170491132

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