Observatorio de I+D+i UPM

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 simul- taneously 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
Nombre congreso	Sustainability in Energy and Buildings
Tipo de participación	960
Lugar del congreso
Revisores	Si
ISBN o ISSN	1876-6102
DOI	10.1016/j.egypro.2014.12.402
Fecha inicio congreso	25/06/2014
Fecha fin congreso	27/06/2014
Desde la página	401
Hasta la página	410
Título de las actas	6th International Conference on Sustainability in Energy and Buildings

Esta actividad pertenece a memorias de investigación

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

• Creador: Grupo de Investigación: Laboratorio de Sistemas Integrados (LSI)
• Departamento: Ingeniería Electrónica