W-LLC: Weighted low-energy localized clustering for embedded networked sensors

Joongheon Kim, Wonjun Lee, Eunkyo Kim, Choonhwa Lee

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

Abstract

This paper addresses a weighted dynamic localized clustering unique to a hierarchical sensor network structure, while reducing the energy consumption of cluster heads and as a result prolonging the network lifetime. Low-Energy Localized Clustering, our previous work, dynamically regulates the radii of clusters to minimize energy consumption of cluster heads while the network field is being covered. We present weighted Low-Energy Localized Clustering (w-LLC), which consumes less energy than LLC with weight functions.

Original languageEnglish
Title of host publicationFuzzy Systems and Knowledge Discovery - Second International Conference, FSKD 2005, Proceedings
PublisherSpringer Verlag
Pages1162-1165
Number of pages4
ISBN (Print)9783540283317
Publication statusPublished - 2006 Jan 1
Event2nd International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2005 - Changsa, China
Duration: 2005 Aug 272005 Aug 29

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3614 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other2nd International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2005
CountryChina
CityChangsa
Period05/8/2705/8/29

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ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Kim, J., Lee, W., Kim, E., & Lee, C. (2006). W-LLC: Weighted low-energy localized clustering for embedded networked sensors. In Fuzzy Systems and Knowledge Discovery - Second International Conference, FSKD 2005, Proceedings (pp. 1162-1165). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3614 LNAI). Springer Verlag.