Memorias de investigación
Ponencias en congresos:
Deep convolutional neural networks for detecting noisy neighbours in cloud infrastructure.
Año:2017
Áreas de investigación
  • Ciencias de la computación y tecnología informática
Datos
Descripción
Cloud infrastructure in data centers is expected to be one of the main technologies supporting Internet communications in the coming years. Virtualization is employed to achieve the flexibility and dynamicity required by the wide variety of applications used today. Therefore, optimal allocation of virtual machines is key to ensuring performance and efficiency. Noisy neighbor is a term used to describe virtual machines competing for physical resources and thus disturbing each other, a phenomenon that can dramatically degrade their performance. Detecting noisy neighbors using simple thresholding approaches is ineffective. To exploit the time-series nature of cloud monitoring data, we propose an approach based on deep convolutional networks. We test it on real infrastructure data and show it outperforms well-known classifiers in detecting noisy neighbors.
Internacional
Si
Nombre congreso
European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning.
Tipo de participación
960
Lugar del congreso
Brujas, Belgica
Revisores
Si
ISBN o ISSN
978-28-7587-039-1
DOI
Fecha inicio congreso
26/04/2017
Fecha fin congreso
28/04/2017
Desde la página
571
Hasta la página
576
Título de las actas
ESANN 2017 proceedings, European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning.
Esta actividad pertenece a memorias de investigación
Participantes
Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Grupo de Investigación: Grupo de Modelización Matemática y Biocomputación
  • Departamento: Sistemas Informáticos