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Towards energy-aware autonomic provisioning for virtualized environments

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Francesc GuimAuthors Info & Claims

HPDC '10: Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing

Pages 320 - 323

https://doi.org/10.1145/1851476.1851520

Published: 21 June 2010 Publication History

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Abstract

As energy efficiency and associated costs become key concerns, consolidated and virtualized data centers and clouds are attractive computing platforms for data- and compute-intensive applications. Recently, these platforms are also being considered for more traditional high-performance computing (HPC) applications. However, maximizing energy efficiency, cost-effectiveness, and utilization for these applications while ensuring performance and other Quality of Service (QoS) guarantees, requires leveraging important and extremely challenging tradeoffs. These include, for example, the tradeoff between the need to efficiently create and provision Virtual Machines (VMs) on data center resources and the need to accommodate the heterogeneous resource demands and runtimes of the applications that run on them. In this paper we propose an energy-aware online provisioning approach for HPC applications on consolidated and virtualized computing platforms. Energy efficiency is achieved using a workload-aware, just-right dynamic provisioning mechanism and the ability to power down subsystems of a host system that are not required by the VMs mapped to it. Our preliminary evaluations show that our approach can improve energy efficiency with an acceptable QoS penalty.

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Aqlan Alhammadi ARaman JMosleh MAli Abdullah H(2023)Comparison of Multiple Regression Particle Swarm Optimization Algorithms and Multiple Regression Multi-Objective Seven-Spot Ladybird Optimization for Host Overload / Under-Loaded Detection in Cloud Datacenter2023 3rd International Conference on Emerging Smart Technologies and Applications (eSmarTA)10.1109/eSmarTA59349.2023.10293580(01-06)Online publication date: 10-Oct-2023
https://doi.org/10.1109/eSmarTA59349.2023.10293580
Dogani JKhunjush FSeydali M(2023)Host load prediction in cloud computing with Discrete Wavelet Transformation (DWT) and Bidirectional Gated Recurrent Unit (BiGRU) networkComputer Communications10.1016/j.comcom.2022.11.018198(157-174)Online publication date: Jan-2023
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Xiao PLiu D(2018)An energy-efficient virtual machine scheduler with I/O collective mechanism in resource virtualisation environmentsInternational Journal of Networking and Virtual Organisations10.1504/IJNVO.2013.06445813:4(311-326)Online publication date: 17-Dec-2018
https://dl.acm.org/doi/10.1504/IJNVO.2013.064458
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Towards energy-aware autonomic provisioning for virtualized environments

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Published In

HPDC '10: Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing

June 2010

911 pages

ISBN:9781605589428

DOI:10.1145/1851476

General Chairs:
Salim Hariri
University of Arizona
,
Kate Keahey
University of Chicago

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

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Published: 21 June 2010

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University of Arizona
SIGARCH

HPDC '10: The 19th International Symposium on High Performance Distributed Computing

June 21 - 25, 2010

Illinois, Chicago

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Aqlan Alhammadi ARaman JMosleh MAli Abdullah H(2023)Comparison of Multiple Regression Particle Swarm Optimization Algorithms and Multiple Regression Multi-Objective Seven-Spot Ladybird Optimization for Host Overload / Under-Loaded Detection in Cloud Datacenter2023 3rd International Conference on Emerging Smart Technologies and Applications (eSmarTA)10.1109/eSmarTA59349.2023.10293580(01-06)Online publication date: 10-Oct-2023
https://doi.org/10.1109/eSmarTA59349.2023.10293580
Dogani JKhunjush FSeydali M(2023)Host load prediction in cloud computing with Discrete Wavelet Transformation (DWT) and Bidirectional Gated Recurrent Unit (BiGRU) networkComputer Communications10.1016/j.comcom.2022.11.018198(157-174)Online publication date: Jan-2023
https://doi.org/10.1016/j.comcom.2022.11.018
Xiao PLiu D(2018)An energy-efficient virtual machine scheduler with I/O collective mechanism in resource virtualisation environmentsInternational Journal of Networking and Virtual Organisations10.1504/IJNVO.2013.06445813:4(311-326)Online publication date: 17-Dec-2018
https://dl.acm.org/doi/10.1504/IJNVO.2013.064458
Xilong QPeng X(2018)An energy-efficient virtual machine scheduler based on CPU share-reclaiming policyInternational Journal of Grid and Utility Computing10.1504/IJGUC.2015.0688266:2(113-120)Online publication date: 16-Dec-2018
https://dl.acm.org/doi/10.1504/IJGUC.2015.068826
Zhou ZYu JLi FYang F(2018)Virtual machine migration algorithm for energy efficiency optimization in cloud computingConcurrency and Computation: Practice and Experience10.1002/cpe.494230:24Online publication date: 30-Aug-2018
https://doi.org/10.1002/cpe.4942
Singh SChana I(2015)QoS-Aware Autonomic Resource Management in Cloud ComputingACM Computing Surveys10.1145/284388948:3(1-46)Online publication date: 22-Dec-2015
https://dl.acm.org/doi/10.1145/2843889
Dargie W(2014)Estimation of the cost of VM migration2014 23rd International Conference on Computer Communication and Networks (ICCCN)10.1109/ICCCN.2014.6911756(1-8)Online publication date: Aug-2014
https://doi.org/10.1109/ICCCN.2014.6911756
Xiao PHu ZLiu DYan GQu X(2013)Virtual machine power measuring technique with bounded error in cloud environmentsJournal of Network and Computer Applications10.1016/j.jnca.2012.12.00236:2(818-828)Online publication date: 1-Mar-2013
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Liu HJin HXu CLiao X(2013)Performance and energy modeling for live migration of virtual machinesCluster Computing10.1007/s10586-011-0194-316:2(249-264)Online publication date: 1-Jun-2013
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Liu HXu CJin HGong JLiao XMaccabe AThain D(2011)Performance and energy modeling for live migration of virtual machinesProceedings of the 20th international symposium on High performance distributed computing10.1145/1996130.1996154(171-182)Online publication date: 8-Jun-2011
https://dl.acm.org/doi/10.1145/1996130.1996154

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Transparently bridging semantic gap in CPU management for virtualized environments

Applications-aware virtual machine provisioning

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Energy-efficient virtual machine provisioning mechanism in cloud computing environments

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Applications-aware virtual machine provisioning

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