Evidence map›Paper›PMID 42230720›Full record

ArticleScientific reports2026

Fault tolerance in para-line network topologies: theory and applications in smart systems.

Sanaa Ahmed Bajri, Muhammad Ahmad, Muhammad Faheem, Muhammad Naveed Jafar, Alhanouf Alburaikan, Hamiden Abd El-Wahed Khalifa

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Article in Scientific reports, 2026. 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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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Sanaa Ahmed BajriDepartment of Mathematical Sciences, College of Science, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh, 11671, Saudi Arabia. sabajri@pnu.edu.sa.
Muhammad AhmadDepartment of Mathematics, School of Sciences, University of Management and Technology, Lahore, 54770, Pakistan. 15009265003@post.umt.edu.pk.
Muhammad FaheemDepartment of Mathematics, School of Sciences, University of Management and Technology, Lahore, 54770, Pakistan.
Muhammad Naveed JafarDepartment of Mathematics, School of Sciences, University of Management and Technology, Lahore, 54770, Pakistan.
Alhanouf AlburaikanDepartment of Mathematics, College of Science, Qassim University, Buraydah, 51452, Saudi Arabia.
Hamiden Abd El-Wahed KhalifaDepartment of Mathematics, College of Science, Qassim University, Buraydah, 51452, Saudi Arabia.

Funding

This research is funded by Princess Nourah bint Abdulrahman University Researchers Supporting Project number (PNURSP2026R527), Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia. PNURSP2026R527
6 · The paper itself

Abstract

This study explores the fault-tolerant metric dimension (FTMD) of the para-line network, which is derived from the n-sunlet network, a significant category of networks created by subdividing and transforming cycle-based networks to simulate greater structural complexity. FTMD ensures robust vertex identification even when some nodes fail, a characteristic essential for fault-resilient systems like communication and sensor networks. By rigorously analyzing the structural attributes of these para-line networks, we demonstrate that the FTMD consistently behaves in a specific manner: it is equal to 3 when [Formula: see text] or 6, and 4 otherwise. Our approach includes constructive distance-vector analysis and combinatorial proofs to ensure the smallest possible size of the fault-tolerant resolving set (FTRS). These findings contribute both theoretically and practically, offering new perspectives on the development of resilient network topologies for practical applications such as IoT infrastructure, smart cities, and fault-tolerant distributed systems.

Indexed as

Artificial Intelligence (AI)Complex networksMetric and fault-tolerant dimensionsn-sunlet networkOptimizationSubdivision and para-line networks

Identifiers

PMID42230720
PMCPMC13462437

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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.