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Research Article | Open Access |

Optimal Pragmatic Clustering for Wireless Networks

Author 1: Suzan Basloom Author 2: Nadine Akkari Author 3: Ghadah Aldabbagh
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 10, No. 3 · Published 2019

DOI: https://doi.org/10.14569/IJACSA.2019.0100369

Abstract

Nodes’ clustering in wireless networks is one of the solutions that used to improve network performance. This paper discusses the clustering in wireless networks. Then it presents a novel clustering algorithm named Pragmatic Genetic Algorithm (PGA). It combines two of the well known artificial intelligence techniques: K-means and Genetic algorithm. The proposed algorithm aims at minimizing the execution time of the clustering, especially in time-sensitive wireless networks applications. The performance of PGA has been compared with the classical clustering algorithms, namely, K-means and KGA. The experiments have been conducted using synthetic and real data from public repositories. PGA obtained excellent results in execution and stable accuracy even when the number of nodes was increased.

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How to Cite this Article

Basloom, S., Akkari, N., & Aldabbagh, G. (2019). Optimal Pragmatic Clustering for Wireless Networks. International Journal of Advanced Computer Science and Applications, 10(3). https://doi.org/10.14569/IJACSA.2019.0100369

Basloom, Suzan, et al.. "Optimal Pragmatic Clustering for Wireless Networks." International Journal of Advanced Computer Science and Applications, vol. 10, no. 3, 2019, https://doi.org/10.14569/IJACSA.2019.0100369.

@article{Basloom2019,
  title     = {Optimal Pragmatic Clustering for Wireless Networks},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {10},
  number    = {3},
  year      = {2019},
  publisher = {The Science and Information Organization},
  author    = {Suzan Basloom and Nadine Akkari and Ghadah Aldabbagh},
  doi       = {10.14569/IJACSA.2019.0100369},
  url       = {https://doi.org/10.14569/IJACSA.2019.0100369}
}

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