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Enhanced Pelican Optimization Algorithm for Cluster Head Selection in Heterogeneous Wireless Sensor Networks.

Zhen Wang1, Jin Duan1, Haobo Xu1

  • 1School of Electronic Information Engineering, Changchun University of Science and Technology, Changchun 130022, China.

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|September 28, 2023
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Summary
This summary is machine-generated.

This study introduces an Enhanced Pelican Optimization Algorithm for Cluster Head Selection (EPOA-CHS) to improve energy efficiency in heterogeneous wireless sensor networks. The new method enhances cluster head selection, extending network lifetime and performance.

Keywords:
cluster head selectionenergy efficientheterogeneous wireless sensor networkspelican optimization algorithm

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Area of Science:

  • Wireless Sensor Networks
  • Optimization Algorithms
  • Network Energy Efficiency

Background:

  • Clustering is vital for energy saving in wireless sensor networks (WSNs).
  • Existing methods struggle with node heterogeneity and energy balance in WSNs.
  • Effective cluster head selection is key to optimizing WSN performance and longevity.

Purpose of the Study:

  • To propose an Enhanced Pelican Optimization Algorithm for Cluster Head Selection (EPOA-CHS).
  • To address challenges in energy balance, node heterogeneity, and algorithm efficiency in WSN clustering.
  • To improve the selection of optimal cluster heads for enhanced network performance.

Main Methods:

  • The Enhanced Pelican Optimization Algorithm (EPOA-CHS) integrates Levy flight with the traditional POA.
  • Population initialization utilizes logistic-sine chaotic mapping.
  • A novel fitness function is employed for appropriate cluster head selection.

Main Results:

  • Simulations with 100 nodes across four heterogeneous scenarios were conducted in MATLAB.
  • EPOA-CHS demonstrated superior performance in total residual energy, network survival time, and surviving nodes.
  • The proposed method significantly improved network throughput compared to existing protocols.

Conclusions:

  • EPOA-CHS effectively enhances cluster head selection in heterogeneous WSNs.
  • The algorithm offers a robust solution for energy balance and network longevity.
  • EPOA-CHS outperforms established protocols like SEP, DEEC, Z-SEP, and PSO-ECSM.