Compromise Between Topology Connection, Load Balance and Wireless Sensor Networks’Anomalies (WSN)

Serhii Perepelitsyn; Andriy Perepelitsyn

doi:doi:10.11648/j.ajist.20250902.12

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Compromise Between Topology Connection, Load Balance and Wireless Sensor Networks’Anomalies (WSN)

Serhii Perepelitsyn^*

, Andriy Perepelitsyn

Published in American Journal of Information Science and Technology (Volume 9, Issue 2)

Received: 24 March 2025 Accepted: 6 May 2025 Published: 22 May 2025

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Abstract

The article addresses the challenge of ensuring a compromise between topological connectivity, load balancing, and anomaly detection in Wireless Sensor Networks (WSN). It analyzes current methods and approaches for optimizing the performance of sensor networks under dynamic conditions. The goal of this work is to analyze the interrelationship between these compromise aspects and propose an optimal approach for their integration. The article proposes a combined approach, which enables an optimal trade-off between these characteristics and enhances network interaction efficiency. To ensure the efficient operation of wireless sensor networks (WSN), it is essential to balance three key factors: topological connectivity and stable connectivity, even load distribution and security. Anomaly detection in wireless sensor networks (WSN) is critically important for ensuring their security and reliability. Modern anomaly detection methods include statistical analysis and machine learning techniques. Statistical traffic analysis enables the identification of deviations from normal network behavior, which may indicate anomalies existence. This approach is based on collecting and analyzing network traffic data, such as transmitted data volume, packet frequency, and other parameters. Deviations from established norms can signal potential issues or attacks. Further research in this domain should focus on the development of intelligent algorithms capable of adapting to real-time network changes. The integration of artificial intelligence and machine learning in WSN systems opens new opportunities for improving their efficiency and resilience to environmental changes.

Published in	American Journal of Information Science and Technology (Volume 9, Issue 2)
DOI	10.11648/j.ajist.20250902.12
Page(s)	79-86
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2025. Published by Science Publishing Group

Keywords

Wireless Sensor Networks, Topological Connectivity, Load Balancing, Anomalies Detection, Artificial Intelligence, Neural Networks

References

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APA Style

Perepelitsyn, S., Perepelitsyn, A. (2025). Compromise Between Topology Connection, Load Balance and Wireless Sensor Networks’Anomalies (WSN). American Journal of Information Science and Technology, 9(2), 79-86. https://doi.org/10.11648/j.ajist.20250902.12

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ACS Style

Perepelitsyn, S.; Perepelitsyn, A. Compromise Between Topology Connection, Load Balance and Wireless Sensor Networks’Anomalies (WSN). Am. J. Inf. Sci. Technol. 2025, 9(2), 79-86. doi: 10.11648/j.ajist.20250902.12

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AMA Style

Perepelitsyn S, Perepelitsyn A. Compromise Between Topology Connection, Load Balance and Wireless Sensor Networks’Anomalies (WSN). Am J Inf Sci Technol. 2025;9(2):79-86. doi: 10.11648/j.ajist.20250902.12

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@article{10.11648/j.ajist.20250902.12,
  author = {Serhii Perepelitsyn and Andriy Perepelitsyn},
  title = {Compromise Between Topology Connection, Load Balance and Wireless Sensor Networks’Anomalies (WSN)
},
  journal = {American Journal of Information Science and Technology},
  volume = {9},
  number = {2},
  pages = {79-86},
  doi = {10.11648/j.ajist.20250902.12},
  url = {https://doi.org/10.11648/j.ajist.20250902.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajist.20250902.12},
  abstract = {The article addresses the challenge of ensuring a compromise between topological connectivity, load balancing, and anomaly detection in Wireless Sensor Networks (WSN). It analyzes current methods and approaches for optimizing the performance of sensor networks under dynamic conditions. The goal of this work is to analyze the interrelationship between these compromise aspects and propose an optimal approach for their integration. The article proposes a combined approach, which enables an optimal trade-off between these characteristics and enhances network interaction efficiency. To ensure the efficient operation of wireless sensor networks (WSN), it is essential to balance three key factors: topological connectivity and stable connectivity, even load distribution and security. Anomaly detection in wireless sensor networks (WSN) is critically important for ensuring their security and reliability. Modern anomaly detection methods include statistical analysis and machine learning techniques. Statistical traffic analysis enables the identification of deviations from normal network behavior, which may indicate anomalies existence. This approach is based on collecting and analyzing network traffic data, such as transmitted data volume, packet frequency, and other parameters. Deviations from established norms can signal potential issues or attacks. Further research in this domain should focus on the development of intelligent algorithms capable of adapting to real-time network changes. The integration of artificial intelligence and machine learning in WSN systems opens new opportunities for improving their efficiency and resilience to environmental changes.
},
 year = {2025}
}

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TY - JOUR
T1 - Compromise Between Topology Connection, Load Balance and Wireless Sensor Networks’Anomalies (WSN)

AU - Serhii Perepelitsyn
AU - Andriy Perepelitsyn
Y1 - 2025/05/22
PY - 2025
N1 - https://doi.org/10.11648/j.ajist.20250902.12
DO - 10.11648/j.ajist.20250902.12
T2 - American Journal of Information Science and Technology
JF - American Journal of Information Science and Technology
JO - American Journal of Information Science and Technology
SP - 79
EP - 86
PB - Science Publishing Group
SN - 2640-0588
UR - https://doi.org/10.11648/j.ajist.20250902.12
AB - The article addresses the challenge of ensuring a compromise between topological connectivity, load balancing, and anomaly detection in Wireless Sensor Networks (WSN). It analyzes current methods and approaches for optimizing the performance of sensor networks under dynamic conditions. The goal of this work is to analyze the interrelationship between these compromise aspects and propose an optimal approach for their integration. The article proposes a combined approach, which enables an optimal trade-off between these characteristics and enhances network interaction efficiency. To ensure the efficient operation of wireless sensor networks (WSN), it is essential to balance three key factors: topological connectivity and stable connectivity, even load distribution and security. Anomaly detection in wireless sensor networks (WSN) is critically important for ensuring their security and reliability. Modern anomaly detection methods include statistical analysis and machine learning techniques. Statistical traffic analysis enables the identification of deviations from normal network behavior, which may indicate anomalies existence. This approach is based on collecting and analyzing network traffic data, such as transmitted data volume, packet frequency, and other parameters. Deviations from established norms can signal potential issues or attacks. Further research in this domain should focus on the development of intelligent algorithms capable of adapting to real-time network changes. The integration of artificial intelligence and machine learning in WSN systems opens new opportunities for improving their efficiency and resilience to environmental changes.

VL - 9
IS - 2
ER -

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Serhii Perepelitsyn

Green Optimum LLC, Kyiv, Ukraine

Contact Email

http://orcid.org/0000-0002-3705-7305
Andriy Perepelitsyn

Green Optimum LLC, Kyiv, Ukraine

http://orcid.org/0000-0002-5385-5761

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APA Style

Perepelitsyn, S., Perepelitsyn, A. (2025). Compromise Between Topology Connection, Load Balance and Wireless Sensor Networks’Anomalies (WSN). American Journal of Information Science and Technology, 9(2), 79-86. https://doi.org/10.11648/j.ajist.20250902.12

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ACS Style

Perepelitsyn, S.; Perepelitsyn, A. Compromise Between Topology Connection, Load Balance and Wireless Sensor Networks’Anomalies (WSN). Am. J. Inf. Sci. Technol. 2025, 9(2), 79-86. doi: 10.11648/j.ajist.20250902.12

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AMA Style

Perepelitsyn S, Perepelitsyn A. Compromise Between Topology Connection, Load Balance and Wireless Sensor Networks’Anomalies (WSN). Am J Inf Sci Technol. 2025;9(2):79-86. doi: 10.11648/j.ajist.20250902.12

Copy | Download

@article{10.11648/j.ajist.20250902.12,
  author = {Serhii Perepelitsyn and Andriy Perepelitsyn},
  title = {Compromise Between Topology Connection, Load Balance and Wireless Sensor Networks’Anomalies (WSN)
},
  journal = {American Journal of Information Science and Technology},
  volume = {9},
  number = {2},
  pages = {79-86},
  doi = {10.11648/j.ajist.20250902.12},
  url = {https://doi.org/10.11648/j.ajist.20250902.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajist.20250902.12},
  abstract = {The article addresses the challenge of ensuring a compromise between topological connectivity, load balancing, and anomaly detection in Wireless Sensor Networks (WSN). It analyzes current methods and approaches for optimizing the performance of sensor networks under dynamic conditions. The goal of this work is to analyze the interrelationship between these compromise aspects and propose an optimal approach for their integration. The article proposes a combined approach, which enables an optimal trade-off between these characteristics and enhances network interaction efficiency. To ensure the efficient operation of wireless sensor networks (WSN), it is essential to balance three key factors: topological connectivity and stable connectivity, even load distribution and security. Anomaly detection in wireless sensor networks (WSN) is critically important for ensuring their security and reliability. Modern anomaly detection methods include statistical analysis and machine learning techniques. Statistical traffic analysis enables the identification of deviations from normal network behavior, which may indicate anomalies existence. This approach is based on collecting and analyzing network traffic data, such as transmitted data volume, packet frequency, and other parameters. Deviations from established norms can signal potential issues or attacks. Further research in this domain should focus on the development of intelligent algorithms capable of adapting to real-time network changes. The integration of artificial intelligence and machine learning in WSN systems opens new opportunities for improving their efficiency and resilience to environmental changes.
},
 year = {2025}
}

Copy | Download

TY - JOUR
T1 - Compromise Between Topology Connection, Load Balance and Wireless Sensor Networks’Anomalies (WSN)

VL - 9
IS - 2
ER -

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