Optimized energy efficient clustering in WSNs through modified zebra optimization

Addressing the challenges of energy imbalance and the difficulty in optimizing cluster head selection in clustering protocols for wireless sensor networks (WSNs), this paper proposes a clustering protocol based on an improved zebra optimization algorithm (IZOACP). The method systematically solves th...

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Bibliographic Details
Published in:Scientific reports Vol. 15; no. 1; pp. 37366 - 16
Main Authors: Lan, Yeshen, Kan, Mingqi, Cao, Bingyu, Rao, Chuchu, Zhou, Mingan, Zhou, Peng
Format: Journal Article
Language:English
Published: London Nature Publishing Group UK 27.10.2025
Nature Publishing Group
Nature Portfolio
Subjects:
639/166
639/705
Algorithms
Clustering
Clustering routing
Communication
Data transmission
Design
Energy consumption
Energy efficiency
Humanities and Social Sciences
Internet of Things
Life span
multidisciplinary
Network lifetime
Network topologies
Optimization algorithms
Optimization techniques
Protocol
Science
Science (multidisciplinary)
Sensors
Simulation
Topology
Wireless sensor network
Zebra Optimization Algorithm
Wireless sensor network
Zebra Optimization Algorithm
Energy consumption
Network lifetime
Internet of Things
Clustering routing
ISSN:2045-2322, 2045-2322
Online Access:Get full text
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Summary:Addressing the challenges of energy imbalance and the difficulty in optimizing cluster head selection in clustering protocols for wireless sensor networks (WSNs), this paper proposes a clustering protocol based on an improved zebra optimization algorithm (IZOACP). The method systematically solves the NP-hard problem of cluster head selection by integrating the zebra optimization algorithm (ZOA), Gaussian mutation strategy, and opposition-based learning mechanism, while optimizing the clustering process based on four key metrics: node residual energy, network density, intra-cluster distance, and communication delay. To further enhance data transmission efficiency, a dynamic adaptive inter-cluster routing mechanism is designed, which achieves path dynamic balancing based on node distance, residual energy, and load status. Experimental results demonstrate that, compared to the LEACH, DMaOWOA, and ARSH-FATI-CHS protocols, IZOACP significantly outperforms the comparison schemes in key metrics such as network lifespan (improved by 97.56%), throughput (improved by 93.88%), and transmission delay (reduced by 10.12%). These results validate its superiority in energy consumption control, topology stability, and large-scale monitoring scenarios, providing an efficient and reliable clustering optimization framework for WSN information monitoring systems.
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ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-025-21653-8