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Graph neural networks based anomalous RSSI detectionBertalanič, Blaž ; Vnučec, Matej ; Fortuna, Carolina—In today’s world, modern infrastructures are being equipped with information and communication technologies to create large IoT networks. It is essential to monitor these networks to ensure smooth ... operations by detecting and correcting link failures or abnormal network behaviour proactively, which can otherwise cause interruptions in business operations. This paper presents a novel method for detecting anomalies in wireless links using graph neural networks. The proposed approach involves converting time series data into graphs and training a new graph neural network architecture based on graph attention networks that successfully detects anomalies at the level of individual measurements of the time series data. The model provides competitive results compared to the state of the art while being computationally more efficient with ≈171 times fewer trainable parameters.Source: BalkanCom 2023, 2023 International Balkan Conference on Communications and Networking (BalkanCom) took place 5-8 June 2023 in İstanbul, Turkey [Elektronski vir] (2023, str. [1-5])Type of material - conference contribution ; adult, seriousPublish date - 2023Language - englishCOBISS.SI-ID - 158215683
Author
Bertalanič, Blaž |
Vnučec, Matej |
Fortuna, Carolina
Topics
communication technologies |
IoT networks |
wireless links
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Database name | Field | Year |
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Links to authors' personal bibliographies | Links to information on researchers in the SICRIS system |
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Bertalanič, Blaž | 54683 |
Vnučec, Matej | |
Fortuna, Carolina | 29521 |
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