On energy-aware dynamic clustering for hierarchical sensor networks

Joongheon Kim, Wonjun Lee, Eunkyo Kim, Joonmo Kim, Choonhwa Lee, Sungjin Kim, Sooyeon Kim

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

1 Citation (Scopus)

Abstract

This paper proposes an energy-efficient nonlinear programming based dynamic clustering protocol (NLP-DC) unique to sensor networks to reduce the consumption of energy of cluster heads and to prolong the sensor network lifetime. NLP-DC must cover the entire network, which is another basic functionality of topology control. To achieve these goals, NLP-DC dynamically regulates the radius of each cluster for the purpose of minimizing energy consumption of cluster heads while the entire sensor network field is still being covered by each cluster. We verify both energy-efficiency and guarantee of perfect coverage. Through simulation results, we show that NLP-DC achieves the desired properties.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages460-469
Number of pages10
Volume3823 LNCS
Publication statusPublished - 2005 Dec 1
EventEUC 2005 Workshops: UISW, NCUS, SecUbiq, USN, and TAUES - Nagasaki, Japan
Duration: 2005 Dec 62005 Dec 9

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3823 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

OtherEUC 2005 Workshops: UISW, NCUS, SecUbiq, USN, and TAUES
CountryJapan
CityNagasaki
Period05/12/605/12/9

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ASJC Scopus subject areas

  • Computer Science(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Theoretical Computer Science

Cite this

Kim, J., Lee, W., Kim, E., Kim, J., Lee, C., Kim, S., & Kim, S. (2005). On energy-aware dynamic clustering for hierarchical sensor networks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3823 LNCS, pp. 460-469). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3823 LNCS).