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• W4360977306 abstract "Internet of Things Networks (IOTN) are applied in all sectors as a result of their broad applicability. Even though the performance of IOTN is satisfactory, it still faces various obstacles, including energy constraints, dependability, and security. This work aims to improve the reliability of the network by identifying defective nodes. Defective nodes affect the normal functionality of the entire network; therefore, it is vital to detect the defective nodes, such that the Quality of Service (QoS) is improved. This work detects defective nodes by employing the Reward-and-Punishment Model (RPM) and the hypothetical analysis of Dempster-Shafer (DS) theory. The effectiveness of the proposed work is found to be satisfactory in terms of defective node detection, precision, energy consumption, and network lifetime." @default.
• W4360977306 created "2023-03-30" @default.
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• W4360977306 creator A5086216445 @default.
• W4360977306 date "2023-06-01" @default.
• W4360977306 modified "2023-09-26" @default.
• W4360977306 title "Defective node detection by employing DS theory and RP model for secure internet of things networks" @default.
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• W4360977306 doi "https://doi.org/10.1016/j.measen.2023.100752" @default.
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