An improved particle swarm optimization algorithm for power-efficient wireless sensor networks

Erfu Yang, Ahmet T. Erdogan, Tughrul Arslan, Nick Barton

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

15 Citations (Scopus)

Abstract

This paper presents an improved particle swarm optimization (PSO) algorithm for onboard embedded applications in power-efficient wireless sensor networks (WSNs) and WSN-based security systems. The objective is to keep the main advantages of the standard PSO algorithm, such as simple form, easy implementation, low algorithmic complexity, and low computational burden while the performance and efficiency can be significantly improved. Numerical experiments are performed on a very difficult benchmark function to validate the performance of the improved PSO algorithm. The results show that the improved PSO algorithm outperforms the standard PSO algorithm.

Original languageEnglish
Title of host publicationECSIS Symposium on Bio-inspired, Learning, and Intelligent Systems for Security, 2007. BLISS 2007
EditorsAdrian Stoica, Tughrul Arslan, Daniel Howard, Tai-Hoon Kim, Ahmed El-Rayis
Place of PublicationLos Alamitos, CA.
Pages76-79
Number of pages4
DOIs
Publication statusPublished - 29 Jan 2008
Event2007 ECSIS Symposium on Bio-inspired, Learning, and Intelligent Systems for Security, BLISS 2007 - Edinburgh, United Kingdom
Duration: 9 Aug 200710 Aug 2007

Conference

Conference2007 ECSIS Symposium on Bio-inspired, Learning, and Intelligent Systems for Security, BLISS 2007
CountryUnited Kingdom
CityEdinburgh
Period9/08/0710/08/07

Keywords

  • particle swarm optimisation
  • telecommunication security
  • wireless sensor networks
  • evolutionary computation
  • intelligent networks
  • intelligent sensors
  • monitoring
  • power engineering and energy
  • power system security
  • sensor systems
  • system-on-a-chip

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