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• W4327945715 abstract "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 $${mathcal {O}} (log (N))$$ time for convergence and $${mathcal {O}} (delta ( log N) )$$ for Critical Node detection, N represents the number of IoT devices, and $$delta$$ 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)." @default.
• W4327945715 created "2023-03-21" @default.
• W4327945715 creator A5037311962 @default.
• W4327945715 date "2023-03-20" @default.
• W4327945715 modified "2023-10-10" @default.
• W4327945715 title "Angle Based Critical Nodes Detection (ABCND) for Reliable Industrial Wireless Sensor Networks" @default.
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• W4327945715 doi "https://doi.org/10.1007/s11277-023-10308-4" @default.
• W4327945715 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/37168440" @default.
• W4327945715 hasPublicationYear "2023" @default.
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