Title :
Profiling Energy Consumption of VMs for Green Cloud Computing
Author :
Chen, Qingwen ; Grosso, Paola ; van der Veldt, Karel ; de Laat, Cees ; Hofman, Rutger ; Bal, Henri
Author_Institution :
Syst. & Network Eng. Res. Group, Univ. of Amsterdam, Amsterdam, Netherlands
Abstract :
The Green Clouds project in the Netherlands investigates a system-level approach towards greening High-Performance Computing (HPC) infrastructures and clouds. In this paper we present our initial results in profiling virtual machines with respect to three power metrics, i.e. power, power efficiency and energy, under different high performance computing workloads. We built a linear power model that represents the behavior of a single work node and includes the contribution from individual components, i.e. CPU, memory and HDD, to the total power consumption of a single work node. Our results could be part of a power characterization module integrated into clusters´ monitoring systems, future Green Clouds energy-savvy scheduler would use this monitoring system to support system-level optimization.
Keywords :
cloud computing; optimisation; power aware computing; virtual machines; GreenClouds project; Netherlands; VM; energy consumption profiling; future GreenClouds energy-savvy scheduler; green cloud computing; high-performance computing infrastructures; linear power model; monitoring system; power efficiency; system-level approach; system-level optimization; total power consumption; virtual machines; Benchmark testing; Energy consumption; Green products; Measurement; Memory management; Power demand; Stress; Cloud Computing; Energy-efficient computing; Green Clouds; Kernel-based Virtual Machine (KVM); Power benchmark; Virtualization;
Conference_Titel :
Dependable, Autonomic and Secure Computing (DASC), 2011 IEEE Ninth International Conference on
Conference_Location :
Sydney, NSW
Print_ISBN :
978-1-4673-0006-3
DOI :
10.1109/DASC.2011.131