Profiling Energy Consumption of VMs for Green Cloud Computing

Chen, Qingwen; Grosso, Paola; Veldt, Karel van der; Laat, Cees de; Hofman, Rutger F. H.; Bal, Henri E.

doi:10.1109/dasc.2011.131

Cited by 66 publications

(98 citation statements)

References 8 publications

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“…For cloud users, replacing high-powered computers with low-powered devices will improve energy efficiency. Methods for reducing energy consumption might be simple techniques such as ensuring energy management for servers in the cloud, such as turning them on and off or putting them to sleep [68,79], or more complex techniques such as auto-scaling infrastructure to create greener computing environments [81] or the use of virtualization techniques for better resource management [29,40,43,45,61,78]. Green cloud computing development is influenced by green data center development.…”

Section: Discussion Of the Topics In The Review Articlesmentioning

confidence: 99%

Green Cloud Computing: A Literature Survey

Radu

2017

Symmetry

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Cloud computing is a dynamic field of information and communication technologies (ICTs), introducing new challenges for environmental protection. Cloud computing technologies have a variety of application domains, since they offer scalability, are reliable and trustworthy, and offer high performance at relatively low cost. The cloud computing revolution is redesigning modern networking, and offering promising environmental protection prospects as well as economic and technological advantages. These technologies have the potential to improve energy efficiency and to reduce carbon footprints and (e-)waste. These features can transform cloud computing into green cloud computing. In this survey, we review the main achievements of green cloud computing. First, an overview of cloud computing is given. Then, recent studies and developments are summarized, and environmental issues are specifically addressed. Finally, future research directions and open problems regarding green cloud computing are presented. This survey is intended to serve as up-to-date guidance for research with respect to green cloud computing.

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Section: Discussion Of the Topics In The Review Articlesmentioning

confidence: 99%

Green Cloud Computing: A Literature Survey

Radu

2017

Symmetry

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“…In addition, literature research as well as experimentation proved that the main factor that relates with the energy consumption of a computing system is the CPU utilization [9] [10]. Hence, in this work we calculate the useful work performed by a VM as the product of its CPU utilization on the cloud host by the maximum capacity (in BWIPS, that is, billion whetstone instructions per second) of the same cloud host.…”

Section: Monitoring Phase (I): Assessment Of Eco-efficiency For Runnimentioning

confidence: 99%

“…However, measuring the energy consumption of a single or even several VMs is a challenging task. From a consumer point of view, VMs are a black box whose energy consumption can only be estimated [9]. In order to do so, power usage models are normally used where performance characteristics are being used for the modeling of the energy consumption.…”

Section: State Of the Art And Related Workmentioning

confidence: 99%

“…The CPU capacity on the physical host (cloud server) has been benchmarked through the UnixBench tool at 3560 MWIPS, that is, 3.56 BWIPS. Assuming that within the VMs we execute some CPU intensive applications and considering also the fact that CPU is the driver of energy consumption into computing systems [37] [38] [9], in the following experimentation we have monitored and analyzed the CPU workload in comparison with the eco-efficiency.…”

Section: Evaluation Of Eco-efficiency Assessmentsmentioning

confidence: 99%

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Estimation and forecasting of ecological efficiency of virtual machines

Katsaros

Stichler

Subirats

et al. 2016

Future Generation Computer Systems

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The massive development of the cloud marketplace is leading to an increase in the number of the Data Centers (DCs) globally and eventually to an increase of the CO 2 related footprint. The calculation of the impact of Virtual Machines (VMs) on the environment is a challenging task, not only due to the technical difficulties but also due to the lack of information from the energy providers. The ecological efficiency of a system captures the relationship between the performance of the system with its environmental footprint. In this paper we present a methodology for the estimation and prediction of the ecological efficiency of VMs in private cloud infrastructures. We specifically focus on the information management starting from the energy resources in a region, the energy consumption and the performance of the resources and finally the calculation of ecological efficiency of a VM. To this end, we have designed and implemented a framework through which the ecological efficiency of a running VM can be assessed and the ecological efficiency of a VM to be deployed can be forecasted. The presented framework is being evaluated through several private cloud scenarios with VM deployments in hosts located in Germany.

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“…The authors refunded the power model by separating the contribution of each active domain in a node, either a VM or domain. Chen et al [17] present a study in profiling virtual machines with respect to three power metrics: power, power efficiency and energy, under different high performance computing workloads. The authors proposed a linear power model that represents the behaviour of a single work node and includes the contribution from individual components.…”

Section: Related Workmentioning

confidence: 99%

A Holistic Model of the Performance and the Energy-Efficiency of Hypervisors in an HPC Environment

Guzek

Varrette

Plugaru

et al. 2013

Energy Efficiency in Large Scale Distributed Systems

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SUMMARYVirtualization is emerging as the prominent approach to mutualise the energy consumed by a single server running multiple Virtual Machines (VMs) instances. The efficient utilization of virtualized servers and/or computing resources requires understanding of the overheads in energy consumption and the throughput, especially on high-demanding High Performance Computing (HPC) platforms. In this paper, a novel holistic model for the power of virtualized computing nodes is proposed. Moreover, we create and validate instances of the proposed model using concrete measures taken during a benchmarking process that reflects an HPC usage, i.e. HPCC, IOZone and Bonnie++, conducted using two different hardware configurations on Grid5000 platform, based on Intel and AMD processors, and three widespread virtualization frameworks, namely Xen, KVM, and VMware ESXi. The proposed holistic model of machine power takes into account the impact of utilisation metrics of the machine's components, as well as the employed application, virtualization, and hardware. The model is further derived using tools such as multiple linear regressions or neural networks that prove its elasticity, applicability and accuracy. The purpose of the model is to enable the estimation of energy consumption of virtualized platforms, aiming to make possible the optimization, scheduling or accounting in such systems, or their simulation.

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Profiling Energy Consumption of VMs for Green Cloud Computing

Cited by 66 publications

References 8 publications

Green Cloud Computing: A Literature Survey

Green Cloud Computing: A Literature Survey

Estimation and forecasting of ecological efficiency of virtual machines

A Holistic Model of the Performance and the Energy-Efficiency of Hypervisors in an HPC Environment

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