A Multi-Objective Particle Swarm Optimization for wireless sensor network deployment

Research output: Contribution to journalArticle

Abstract

The use of wireless sensor networks nowadays is imperative for different domain of interests. One of the challenging task in deploying such networks lies on the efficient deployment that guarantees least number of sensors while assuring the connectivity and the coverage among these sensors. This would significantly contribute toward longer lifetime of the network. Several studies have addressed this problem by proposing various meta-heuristic approaches. One of these approaches is the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) which has been extensively used for WSN deployment. However, such approach suffers of the inaccurate fitness values provided for criteria in the same front. Therefore, this paper aims to propose an alternative approach which is called Multi-Objective Particle Swarm Optimization (MOPSO). The proposed method has been compared against the NSGA-II and the results showed that the proposed method has superior performance.

Original languageEnglish
Pages (from-to)140-146
Number of pages7
JournalInternational Journal of Engineering and Technology(UAE)
Volume7
Issue number4.36 Special Issue 36
Publication statusPublished - 1 Jan 2018

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Sorting
Particle swarm optimization (PSO)
Wireless sensor networks
Genetic algorithms
Sensors
Heuristics

Keywords

  • Genetic algorithm
  • Multi-objective
  • Pareto-based
  • Particle swarm optimization
  • Region of interest
  • Wireless sensor network

ASJC Scopus subject areas

  • Biotechnology
  • Computer Science (miscellaneous)
  • Environmental Engineering
  • Chemical Engineering(all)
  • Engineering(all)
  • Hardware and Architecture

Cite this

A Multi-Objective Particle Swarm Optimization for wireless sensor network deployment. / Ibrahem, S.; Ahmad Nazri, Mohd Zakree; Othman, Zalinda.

In: International Journal of Engineering and Technology(UAE), Vol. 7, No. 4.36 Special Issue 36, 01.01.2018, p. 140-146.

Research output: Contribution to journalArticle

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