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In graph theory, '''LASCNN''' is a '''L'''ocalized '''A'''lgorithm for '''S'''egregation of '''C'''ritical/'''N'''on-critical '''N'''odes<ref>Muhammad Imran, Mohamed A. Alnuem, Mahmoud S. Fayed, and Atif Alamri. "Localized algorithm for segregation of critical/non-critical nodes in mobile ad hoc and sensor networks." Procedia Computer Science 19 (2013): 1167–1172.</ref> The algorithm works on the principle of distinguishing between critical and non-critical nodes for network connectivity based on limited topology information.<ref>N. Javaid, A. Ahmad, M. Imran, A. A. Alhamed and M. Guizani, "BIETX: A new quality link metric for Static Wireless Multi-hop Networks," 2016 International Wireless Communications and Mobile Computing Conference (IWCMC), Paphos, 2016, pp. 784–789, {{doi
This algorithm can distinguish the critical nodes of the network with high precision, indeed, accuracy can reach 100% when identifying non-critical nodes.<ref>Zhang, Y.; Zhang, Z.; Zhang, B. A Novel Hybrid Optimization Scheme on Connectivity Restoration Processes for Large Scale Industrial Wireless Sensor and Actuator Networks. Processes 2019, 7, 939. </ref> The performance of LASCNN is scalable and quite competitive compared to other schemes.<ref>Kasali, F. A., Y. A. Adekunle, A. A. Izang, O. Ebiesuwa, and O. Otusile. "Evaluation of Formal Method Usage amongst Babcock University Students in Nigeria." Evaluation 5, no. 1 (2016).</ref>
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==Implementation==
[[File:Critical_Nodes_Application.png|thumb|300px|Critical Nodes Application - An implementation for the LASCNN algorithm using PWCT]]
The Critical Nodes application is a Free Open-Source implementation for the LASCNN algorithm. The application was developed in 2013 using [[
==See also==
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