Implementation of the X-means Clustering Algorithm for Wireless Sensor Networks

Radwan, Abdelrahman; Kamarudin, Nazhatul Hafizah; Solihin, Mahmud Iwan; Ang, Chun Kit; Leong, Hungyang; Rizon, M.

doi:10.5954/icarob.2020.os10-4

Cited by 2 publications

(1 citation statement)

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“…A bad choice of initial centroid leads to unbalanced cluster sizes and unbalanced CHs consumption that causes premature CHs death at the early stage of the network lifetime. Therefore, Radwan et al [23]- [25] proposed the X-mean algorithm in three articles. Their concept is to split k-means centroid (parents) into multiple new positions (children), thus expanding the search space for better positioning and the best number of clusters.…”

Section: Introductionmentioning

confidence: 99%

Fitness function X-means for prolonging wireless sensor networks lifetime

Radwan

Abdellatif²,

Radwan³

et al. 2023

IJECE

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X-means and k-means are clustering algorithms proposed as a solution for prolonging wireless sensor networks (WSN) lifetime. In general, X-means overcomes k-means limitations such as predetermined number of clusters. The main concept of X-means is to create a network with basic clusters called parents and then generate (j) number of children clusters by parents splitting. X-means did not provide any criteria for splitting parent’s clusters, nor does it provide a method to determine the acceptable number of children. This article proposes fitness function X-means (FFX-means) as an enhancement of X-means; FFX-means has a new method that determines if the parent clusters are worth splitting or not based on predefined network criteria, and later on it determines the number of children. Furthermore, FFX-means proposes a new cluster-heads selection method, where the cluster-head is selected based on the remaining energy of the node and the intra-cluster distance. The simulation results show that FFX-means extend network lifetime by 11.5% over X-means and 75.34% over k-means. Furthermore, the results show that FFX-means balance the node’s energy consumption, and nearly all nodes depleted their energy within an acceptable range of simulation rounds.

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Section: Introductionmentioning

confidence: 99%