An Adaptive PSO Approach with Modified Position Equation for Optimizing Critical Node Detection in Large-Scale Networks: Application to Wireless Sensor Networks Article Swipe
Abdelmoujib Megzari
,
Walid Osamy
,
Bader Alwasel
,
Ahmed M. Khedr
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/jsan14030062
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/jsan14030062
In recent years, wireless sensor networks (WSNs) have been employed across various domains, including military services, healthcare, disaster response, industrial automation, and smart infrastructure. Due to the absence of fixed communication infrastructure, WSNs rely on ad hoc connections between sensor nodes to transmit sensed data to target nodes. Within a WSN, a sensor node whose failure partitions the network into disconnected segments is referred to as a critical node or cut vertex. Identifying such nodes is a fundamental step toward ensuring the reliability of WSNs. The critical node detection problem (CNDP) focuses on determining the set of nodes whose removal most significantly affects the network’s connectivity, stability, functionality, robustness, and resilience. CNDP is a significant challenge in network analysis that involves identifying the nodes that have a significant influence on connectivity or centrality measures within a network. However, achieving an optimal solution for the CNDP is often hindered by its time-consuming and computationally intensive nature, especially when dealing with large-scale networks. In response to this challenge, we present a method based on particle swarm optimization (PSO) for the detection of critical nodes. We employ discrete PSO (DPSO) along with the modified position equation (MPE) to effectively solve the CNDP, making it applicable to various k-vertex variations of the problem. We examine the impact of population size on both execution time and result quality. Experimental analysisusing different neighborhood topologies—namely, the star topology and the dynamic topology—was conducted to analyze their impact on solution effectiveness and adaptability to diverse network configurations. We consistently observed better result quality with the dynamic topology compared to the star topology for the same population size, while the star topology exhibited better execution time. Our findings reveal the promising efficacy of the proposed solution in addressing the CNDP, achieving high-quality solutions compared to existing methods.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/jsan14030062
- https://www.mdpi.com/2224-2708/14/3/62/pdf?version=1750065345
- OA Status
- gold
- Cited By
- 1
- References
- 81
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4411343440
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4411343440Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.3390/jsan14030062Digital Object Identifier
- Title
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An Adaptive PSO Approach with Modified Position Equation for Optimizing Critical Node Detection in Large-Scale Networks: Application to Wireless Sensor NetworksWork title
- Type
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articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2025Year of publication
- Publication date
-
2025-06-16Full publication date if available
- Authors
-
Abdelmoujib Megzari, Walid Osamy, Bader Alwasel, Ahmed M. KhedrList of authors in order
- Landing page
-
https://doi.org/10.3390/jsan14030062Publisher landing page
- PDF URL
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https://www.mdpi.com/2224-2708/14/3/62/pdf?version=1750065345Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
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https://www.mdpi.com/2224-2708/14/3/62/pdf?version=1750065345Direct OA link when available
- Concepts
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Computer science, Wireless sensor network, Position (finance), Node (physics), Scale (ratio), Computer network, Acoustics, Economics, Physics, Quantum mechanics, FinanceTop concepts (fields/topics) attached by OpenAlex
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1Total citation count in OpenAlex
- Citations by year (recent)
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2025: 1Per-year citation counts (last 5 years)
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81Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| primary_location.source.host_organization_lineage_names | Multidisciplinary Digital Publishing Institute |
| primary_location.license | cc-by |
| primary_location.pdf_url | https://www.mdpi.com/2224-2708/14/3/62/pdf?version=1750065345 |
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| primary_location.raw_source_name | Journal of Sensor and Actuator Networks |
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| publication_date | 2025-06-16 |
| publication_year | 2025 |
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