Journal of Network and Systems Management

, Volume 25, Issue 1, pp 21–46 | Cite as

A Genetic Algorithm-Based, Dynamic Clustering Method Towards Improved WSN Longevity

  • Xiaohui Yuan
  • Mohamed Elhoseny
  • Hamdy K. El-Minir
  • Alaa M. Riad
Article

Abstract

The dynamic nature of wireless sensor networks (WSNs) and numerous possible cluster configurations make searching for an optimal network structure on-the-fly an open challenge. To address this problem, we propose a genetic algorithm-based, self-organizing network clustering (GASONeC) method that provides a framework to dynamically optimize wireless sensor node clusters. In GASONeC, the residual energy, the expected energy expenditure, the distance to the base station, and the number of nodes in the vicinity are employed in search for an optimal, dynamic network structure. Balancing these factors is the key of organizing nodes into appropriate clusters and designating a surrogate node as cluster head. Compared to the state-of-the-art methods, GASONeC greatly extends the network life and the improvement up to 43.44 %. The node density greatly affects the network longevity. Due to the increased distance between nodes, the network life is usually shortened. In addition, when the base station is placed far from the sensor field, it is preferred that more clusters are formed to conserve energy. The overall average time of GASONeC is 0.58 s with a standard deviation of 0.05.

Keywords

Wireless sensor networks Genetic algorithms Clustering Energy consumption 

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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Xiaohui Yuan
    • 1
    • 2
  • Mohamed Elhoseny
    • 2
    • 3
  • Hamdy K. El-Minir
    • 4
  • Alaa M. Riad
    • 3
  1. 1.College of Information and EngineeringChina University of GeosciencesWuhanChina
  2. 2.Department of Computer Science and EngineeringUniversity of North TexasDentonUSA
  3. 3.Department of Information SystemsMansoura UniversityMansouraEgypt
  4. 4.Department of Electrical EngineeringKafr El-Sheikh UniversityKafr El-SheikhEgypt

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