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Neutrosophic and Information Fusion

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Online: 2836-7863
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Neutrosophic and Information Fusion
Full Length Article

Volume 6Issue 2PP: 12–16 • 2026

Trust-Aware Cluster-Head Selection in IoT Wireless Sensor Networks via Interval-Neutrosophic Information Fusion

Durdona Uktamova 1* ,
Adnan Manzoor 2
1Faculty of Joint Degree, Tashkent State University of Economics, Uzbekistan
2Faculty of Engineering, Central Asian University, Uzbekistan
* Corresponding Author.
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© 2026 The Author(s). Published by ASPG. This article is licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0).

Received: August 14, 2025 Revised: Accepted: November 20, 2025

Abstract

Cluster-based routing extends the lifetime of an Internet-of-Things wireless sensor network (WSN), but the quality of a cluster head (CH) depends on several mutually uncertain factors—residual energy, link quality, centrality and behavioural trust—each measured imperfectly and reported as a range rather than a point. We model each candidate node with an interval-neutrosophic set (INS), so every factor carries an interval of truth, indeterminacy and falsity, and we fuse the factors with an interval-neutrosophic weighted aggregation operator into a single suitability score. Cluster heads are then elected by a possibility-degree ranking of the fused interval scores, subject to a minimum-trust guard. Simulation of a 200-node network shows that interval-neutrosophic CH selection extends first-node-death time by 18–24% over a standard energy-and-distance heuristic and cuts the share of misbehaving nodes elected as heads from 14.7% to 1.3%. The method degrades gracefully as measurement indeterminacy grows and adds only modest per-round overhead.

Keywords

Interval-neutrosophic sets Information fusion Wireless sensor networks Cluster-head selection Trust Energy efficiency

References

[1] W. Heinzelman, A. Chandrakasan, and H. Balakrishnan, “An application-specific protocol architecture for wireless microsensor networks,” IEEE Transactions on Wireless Communications, vol. 1, no. 4, pp. 660–670, 2002.

[2] O. Younis and S. Fahmy, “HEED: A hybrid, energyefficient, distributed clustering approach for ad hoc sensor networks,” IEEE Transactions on Mobile Computing, vol. 3, no. 4, pp. 366–379, 2004.

[3] T. Kaur and D. Kumar, “Particle swarm optimizationbased unequal and fault tolerant clustering protocol for wireless sensor networks,” IEEE Sensors Journal, vol. 18, no. 11, pp. 4614–4622, 2018.

[4] J.-S. Lee and W.-L. Cheng, “Fuzzy-logic-based clustering approach for wireless sensor networks using energy predication,” IEEE Sensors Journal, vol. 12, no. 9, pp. 2891–2897, 2012.

[5] G. Han, J. Jiang, L. Shu, J. Niu, and H.-C. Chao, “Management and applications of trust in wireless sensor networks: A survey,” Journal of Computer and System Sciences, vol. 80, no. 3, pp. 602–617, 2014.

[6] S. Ganeriwal, L. K. Balzano, and M. B. Srivastava, “Reputation-based framework for high integrity sensor networks,” ACM Transactions on Sensor Networks, vol. 4, no. 3, pp. 15:1–15:37, 2008.

[7] H. Wang, Y. Zhang, F. Smarandache, and R. Sunderraman, Interval Neutrosophic Sets and Logic. Hexis, 2005.

[8] J. Ye, “Similarity measures between interval neutrosophic sets and their applications in multicriteria decision-making,” Journal of Intelligent & Fuzzy Systems, vol. 26, no. 1, pp. 165–172, 2014.

[9] P. Biswas, S. Pramanik, and B. C. Giri, “TOPSIS method for multi-attribute group decision-making under single-valued neutrosophic environment,” Neural Computing and Applications, vol. 27, no. 3, pp. 727–737, 2016.

[10] S. Broumi, A. Bakali, M. Talea, and F. Smarandache, “Shortest path problem under interval-valued neutrosophic setting,” International Journal of Advanced Trends in Computer Science and Engineering, vol. 8, pp. 216–222, 2019.

[11] A. Aziz, K. Singh, W. Osamy, and A. M. Khedr, “Effective algorithm for optimizing compressive sensing in IoT and periodic monitoring applications,” Journal of Network and Computer Applications, vol. 126, pp. 12–28, 2019.

[12] R. Sahin and A. Kucuk, “Subsethood measure for single valued neutrosophic sets,” Journal of Intelligent & Fuzzy Systems, vol. 29, no. 2, pp. 525–530, 2015.

Cite This Article

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Uktamova, Durdona, Manzoor, Adnan . "Trust-Aware Cluster-Head Selection in IoT Wireless Sensor Networks via Interval-Neutrosophic Information Fusion." Neutrosophic and Information Fusion, vol. Volume 6, no. Issue 2, 2026, pp. 12–16. DOI: https://doi.org/10.54216/NIF.060203
Uktamova, D., Manzoor, A. (2026). Trust-Aware Cluster-Head Selection in IoT Wireless Sensor Networks via Interval-Neutrosophic Information Fusion. Neutrosophic and Information Fusion, Volume 6(Issue 2), 12–16. DOI: https://doi.org/10.54216/NIF.060203
Uktamova, Durdona, Manzoor, Adnan . "Trust-Aware Cluster-Head Selection in IoT Wireless Sensor Networks via Interval-Neutrosophic Information Fusion." Neutrosophic and Information Fusion Volume 6, no. Issue 2 (2026): 12–16. DOI: https://doi.org/10.54216/NIF.060203
Uktamova, D., Manzoor, A. (2026) 'Trust-Aware Cluster-Head Selection in IoT Wireless Sensor Networks via Interval-Neutrosophic Information Fusion', Neutrosophic and Information Fusion, Volume 6(Issue 2), pp. 12–16. DOI: https://doi.org/10.54216/NIF.060203
Uktamova D, Manzoor A. Trust-Aware Cluster-Head Selection in IoT Wireless Sensor Networks via Interval-Neutrosophic Information Fusion. Neutrosophic and Information Fusion. 2026;Volume 6(Issue 2):12–16. DOI: https://doi.org/10.54216/NIF.060203
D. Uktamova, A. Manzoor, "Trust-Aware Cluster-Head Selection in IoT Wireless Sensor Networks via Interval-Neutrosophic Information Fusion," Neutrosophic and Information Fusion, vol. Volume 6, no. Issue 2, pp. 12–16, 2026. DOI: https://doi.org/10.54216/NIF.060203
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