A Bio-Inspired Algorithm for Performance Optimization in Wireless Sensor Networks

Chi-Tsun Cheng, Chi K. Tse, Francis C. M. Lau

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

Abstract

A wireless sensor network typically comprises a number of inexpensive power constrained sensors which collect data from the sensing environment and transmit them towards the base station in a coordinated way. Employing techniques of clustering and election of cluster heads can increase the transmission efficiency and prolong the network lifetime. This paper proposes a bio-inspired de-centralized clustering algorithm for wireless sensor networks. The clustering algorithm is evaluated assuming a first-order radio model. Simulation results show that the proposed algorithm brings a 16 % to 161 % improvement over other de-centralized clustering algorithms in terms of network lifetime. Simulation results also show that the proposed de-centralized clustering algorithm has a similar performance as the centralized clustering algorithm.
Original languageEnglish
Title of host publication2007 International Symposium on Nonlinear Theory and Its Applications, NOLTA'07
Pages309-312
DOIs
Publication statusPublished - Sept 2007
Externally publishedYes
Event2007 International Symposium on Nonlinear Theory and its Applications (NOLTA'07) - Vancouver, Canada
Duration: 16 Sept 200719 Sept 2007

Publication series

NameIEICE Proceeding Series
ISSN (Electronic)2188-5079

Conference

Conference2007 International Symposium on Nonlinear Theory and its Applications (NOLTA'07)
Abbreviated titleNOLTA 2007
PlaceCanada
CityVancouver
Period16/09/0719/09/07

Research Keywords

  • bio-inspired algorithm
  • clustering
  • decentralized control
  • wireless sensor networks

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