Memorias de investigación
Artículos en revistas:
Server Power Modeling for Run-time Energy Optimization of Cloud Computing Facilities
Año:2014

Áreas de investigación
  • Tecnología electrónica y de las comunicaciones

Datos
Descripción
As advanced Cloud services are becoming mainstream, the contribution of data centers in the overall power consumption of modern cities is growing dramatically. The average consumption of a single data center is equivalent to the energy consumption of 25.000 households. Modeling the power consumption for these infrastructures is crucial to anticipate the effects of aggressive optimization policies, but accurate and fast power modeling is a complex challenge for high-end servers not yet satisfied by analytical approaches. This work proposes an automatic method, based on Multi-Objective Particle Swarm Optimization, for the identification of power models of enterprise servers in Cloud data centers. Our approach, as opposed to previous procedures, does not only consider the workload consolidation for deriving the power model, but also incorporates other non traditional factors like the static power consumption and its dependence with temperature. Our experimental results shows that we reach slightly better models than classical approaches, but simultaneously simplifying the power model structure and thus the numbers of sensors needed, which is very promising for a short-term energy prediction. This work, validated with real Cloud applications, broadens the possibilities to derive efficient energy saving techniques for Cloud facilities.
Internacional
Si
JCR del ISI
No
Título de la revista
Energy Procedia
ISSN
1876-6102
Factor de impacto JCR
Información de impacto
Volumen
DOI
Número de revista
Desde la página
401
Hasta la página
410
Mes
SIN MES
Ranking

Esta actividad pertenece a memorias de investigación

Participantes
  • Autor: Patricia Arroba Garcia UPM
  • Autor: Jose Luis Risco-Martin Universidad Complutense de Madrid
  • Autor: Marina Zapater Sancho UPM
  • Autor: Jose Manuel Moya Fernandez UPM
  • Autor: Jose Luis Ayala Universidad Complutense de Madrid
  • Autor: Katzalin Olcoz Universidad Complutense de Madrid

Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Grupo de Investigación: Laboratorio de Sistemas Integrados (LSI)
  • Departamento: Ingeniería Electrónica