Evidence map›Paper›PMID 41258047›Full record

ArticleScientific reports2025

Optimizing wireless sensor networks using fuzzy triangular snake graph models and fuzzy topological indices.

Atef F Hashem, Shama Liaqat, Zeeshan Saleem Mufti, Muhammad Farhan Hanif

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Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

4 authors.

Atef F HashemDepartment of Mathematics and Statistics, College of Science, Imam Mohammad Ibn Saud Islamic University (IMSIU), 11432, Riyadh, Saudi Arabia.
Shama LiaqatDepartment of Mathematics and Statistics, The University of Lahore, Lahore Campus, Lahore, Pakistan.
Zeeshan Saleem MuftiDepartment of Mathematics and Statistics, The University of Lahore, Lahore Campus, Lahore, Pakistan.
Muhammad Farhan HanifDepartment of Mathematics and Statistics, The University of Lahore, Lahore Campus, Lahore, Pakistan. farhanlums@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This research focuses on a detailed investigation of advanced fuzzy indices applied to enhanced version of triangular snake graph, designated as fuzzy triangular snake graph ([Formula: see text]). Its practical applications in wireless sensor network (WSN) is also designed. We derive closed-form formulas for several fuzzy indices, including first and second fuzzy Zagreb indices, fuzzy Harmonic, Randić, Misbalance Prodeg, Nirmala, along with Sombor indices. By applying these indices to a WSN modeled with redundant triangular connectivity, we evaluate the network's structural efficiency, robustness, and fault tolerance. The computed results reveal that the fuzzy triangular snake topology ensures balanced node connectivity, minimizes energy imbalance, and enhances the network's ability to maintain reliable communication in the presence of node failures and uncertainties. The results confirm the applicability of the fuzzy triangular snake model in optimization of energy- and resilient WSNs, thus drawing a high degree of correlation between such contemporary graph theory, as fuzziness, and the design of a modern communication network.

Identifiers

PMID41258047
PMCPMC12630692

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.