Energy efficient in-network phase RFID data filtering scheme

Dong Sub Kim, Ali Kashif, Xue Ming, Jung Hwan Kim, Myong Soon Park

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

10 Citations (Scopus)

Abstract

One of the limitations that prevent proliferation of RFID technology is redundant data transmission within the network usually caused by unreliability of readers and duplicate readings generated by adjacent readers. Such redundancies unnecessarily consume resources of network and depreciate the performance of RFID installation. In this paper, we propose a CLIF, an energy-efficient filtering scheme that detects the in-network redundant data and eliminates it. The simulation results show that the CLIF significantly reduces the number of comparisons required for detecting duplicates while it achieves relatively high duplicate data elimination ratio considering the location of reader. Consequently, CLIF reduces the considerable amount of transmission within the network.

Original languageEnglish
Title of host publicationUbiquitous Intelligence and Computing - 5th International Conference, UIC 2008, Proceedings
Pages311-322
Number of pages12
DOIs
Publication statusPublished - 2008
Event5th International Conference on Ubiquitous Intelligence and Computing, UIC 2008 - Oslo, Norway
Duration: 2008 Jun 232008 Jun 25

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5061 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other5th International Conference on Ubiquitous Intelligence and Computing, UIC 2008
CountryNorway
CityOslo
Period08/6/2308/6/25

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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    Kim, D. S., Kashif, A., Ming, X., Kim, J. H., & Park, M. S. (2008). Energy efficient in-network phase RFID data filtering scheme. In Ubiquitous Intelligence and Computing - 5th International Conference, UIC 2008, Proceedings (pp. 311-322). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5061 LNCS). https://doi.org/10.1007/978-3-540-69293-5_25