Descripción
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In this research we propose an ANN predictive power model for GPU-based federated edge data centers based on data traffic demanded by the application. We validate our approach, using real traffic for a state-of-the-art driving assistance application, obtaining 1 hour ahead power predictions with a normalized root-mean-square deviation below 7.4% when compared with real measurements. Our research would help to optimize both resource management and sizing of edge federations. | |
Internacional
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Si |
Nombre congreso
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2019 IEEE International Smart Cities Conference |
Tipo de participación
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960 |
Lugar del congreso
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Casablanca, Marruecos |
Revisores
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Si |
ISBN o ISSN
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978-1-7281-0846-9 |
DOI
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10.1109/ISC246665.2019.9071685 |
Fecha inicio congreso
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14/10/2019 |
Fecha fin congreso
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17/10/2019 |
Desde la página
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454 |
Hasta la página
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459 |
Título de las actas
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Proceedings of the 5th IEEE International Smart Cities Conference (IEEE ISC2 2019) |