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Wireless Sensor Network (WSN) Energy-Efficient Clustering and Routing: Evaluating Kepler’s Algorithm Alongside K-Means

Mahmoud Shakir Wahhab

2025enwireless sensor networksenergy efficiencyclusteringroutingk-meansoptimization algorithms

Abstract

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Wireless Sensor Networks (WSNs) are widely used in domains such as military surveillance and environmental monitoring, where strict energy constraints on sensor nodes make energy-efficient operation essential. This work proposes and evaluates a hybrid approach that integrates Kepler’s Algorithm, inspired by planetary motion dynamics, with K-means clustering to improve both clustering and routing efficiency in WSNs. K-means is employed to form spatially efficient clusters of sensor nodes, while Kepler’s Algorithm is used to select low-energy, stable routing paths based on elliptical orbit principles. The proposed method is assessed through extensive simulations of WSN environments, examining metrics such as energy consumption, network lifetime, and data transmission efficiency. Results show notable gains in energy efficiency and significant extension of network lifetime compared to conventional protocols. The findings demonstrate that combining Kepler’s Algorithm with K-means clustering offers an effective solution for energy-aware clustering and routing in WSNs.

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Cite This Work

@article{98ba8002-1d94-47a9-a9d2-d1a4bca82935,
  title={Wireless Sensor Network (WSN) Energy-Efficient Clustering and Routing:  Evaluating Kepler’s Algorithm Alongside K-Means  },
  author={Mahmoud Shakir Wahhab},
  year={2025},
  language={en}
}
TY  - JOUR
TI  - Wireless Sensor Network (WSN) Energy-Efficient Clustering and Routing:  Evaluating Kepler’s Algorithm Alongside K-Means  
AU  - Mahmoud Shakir Wahhab
PY  - 2025
LA  - en
ER  -

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