A bio-inspired algorithm for performance optimization in wireless sensor networks

C.T. Cheng, Chi Kong Tse, Chung Ming Lau

Research output: Unpublished conference presentation (presented paper, abstract, poster)Conference presentation (not published in journal/proceeding/book)Academic researchpeer-review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
Pages309-312
Number of pages4
Publication statusPublished - 2007
EventInternational Symposium on Nonlinear Theory and Its Applications [NOLTA] -
Duration: 1 Jan 2007 → …

Conference

ConferenceInternational Symposium on Nonlinear Theory and Its Applications [NOLTA]
Period1/01/07 → …

Keywords

  • Bio-inspired algorithm
  • Clustering
  • Decentralized control
  • Wireless sensor networks

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