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Angle Based Critical Nodes Detection (ABCND) for Reliable Industrial Wireless Sensor Networks
Node failure in the Wireless Sensor Networks (WSN) topology may lead to economic loss, endanger people, and cause environmental damage. Node reliability can be achieved by adequately managing network topology using structural approaches, where the critical nodes are precisely detected and protected....
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10026242/ https://www.ncbi.nlm.nih.gov/pubmed/37168440 http://dx.doi.org/10.1007/s11277-023-10308-4 |
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author | Shukla, Shailendra |
author_facet | Shukla, Shailendra |
author_sort | Shukla, Shailendra |
collection | PubMed |
description | Node failure in the Wireless Sensor Networks (WSN) topology may lead to economic loss, endanger people, and cause environmental damage. Node reliability can be achieved by adequately managing network topology using structural approaches, where the critical nodes are precisely detected and protected. This paper addresses the problem of critical node detection and presents two-phase algorithms (ABCND). Phase-I, a 2D Critical Node (C-N) detection algorithm, is proposed, which uses only the neighbor’s Received Signal Strength Indicator (RSSI) information. In Phase II, a correlation-based reliable RSSI approach is proposed to increase the node resilience against the adversary. The proposed algorithms (ABCND) require [Formula: see text] time for convergence and [Formula: see text] for Critical Node detection, N represents the number of IoT devices, and [Formula: see text] is the cost required to forward the message. We compare our algorithm (ABCND) with the current state-of-the-art on C-N detection algorithms. The simulation result shows that the proposed ABCND algorithm consumes 50% less energy to detect C-N with 90% to 95% accurate Critical Nodes (C-N). |
format | Online Article Text |
id | pubmed-10026242 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-100262422023-03-21 Angle Based Critical Nodes Detection (ABCND) for Reliable Industrial Wireless Sensor Networks Shukla, Shailendra Wirel Pers Commun Article Node failure in the Wireless Sensor Networks (WSN) topology may lead to economic loss, endanger people, and cause environmental damage. Node reliability can be achieved by adequately managing network topology using structural approaches, where the critical nodes are precisely detected and protected. This paper addresses the problem of critical node detection and presents two-phase algorithms (ABCND). Phase-I, a 2D Critical Node (C-N) detection algorithm, is proposed, which uses only the neighbor’s Received Signal Strength Indicator (RSSI) information. In Phase II, a correlation-based reliable RSSI approach is proposed to increase the node resilience against the adversary. The proposed algorithms (ABCND) require [Formula: see text] time for convergence and [Formula: see text] for Critical Node detection, N represents the number of IoT devices, and [Formula: see text] is the cost required to forward the message. We compare our algorithm (ABCND) with the current state-of-the-art on C-N detection algorithms. The simulation result shows that the proposed ABCND algorithm consumes 50% less energy to detect C-N with 90% to 95% accurate Critical Nodes (C-N). Springer US 2023-03-20 2023 /pmc/articles/PMC10026242/ /pubmed/37168440 http://dx.doi.org/10.1007/s11277-023-10308-4 Text en © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Article Shukla, Shailendra Angle Based Critical Nodes Detection (ABCND) for Reliable Industrial Wireless Sensor Networks |
title | Angle Based Critical Nodes Detection (ABCND) for Reliable Industrial Wireless Sensor Networks |
title_full | Angle Based Critical Nodes Detection (ABCND) for Reliable Industrial Wireless Sensor Networks |
title_fullStr | Angle Based Critical Nodes Detection (ABCND) for Reliable Industrial Wireless Sensor Networks |
title_full_unstemmed | Angle Based Critical Nodes Detection (ABCND) for Reliable Industrial Wireless Sensor Networks |
title_short | Angle Based Critical Nodes Detection (ABCND) for Reliable Industrial Wireless Sensor Networks |
title_sort | angle based critical nodes detection (abcnd) for reliable industrial wireless sensor networks |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10026242/ https://www.ncbi.nlm.nih.gov/pubmed/37168440 http://dx.doi.org/10.1007/s11277-023-10308-4 |
work_keys_str_mv | AT shuklashailendra anglebasedcriticalnodesdetectionabcndforreliableindustrialwirelesssensornetworks |