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research-article

Utilizing green energy prediction to schedule mixed batch and service jobs in data centers

Authors:

Jagannathan Venkatesh,

Tajana RosingAuthors Info & Claims

ACM SIGOPS Operating Systems Review, Volume 45, Issue 3

Pages 53 - 57

https://doi.org/10.1145/2094091.2094105

Published: 11 January 2012 Publication History

Abstract

As brown energy costs grow, renewable energy becomes more widely used. Previous work focused on using immediately available green energy to supplement the non-renewable, or brown energy at the cost of canceling and rescheduling jobs whenever the green energy availability is too low [16]. In this paper we design an adaptive data center job scheduler which utilizes short term prediction of solar and wind energy production. This enables us to scale the number of jobs to the expected energy availability, thus reducing the number of cancelled jobs by 4x and improving green energy usage efficiency by 3x over just utilizing the immediately available green energy.

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Cited By

Liu WWei KYan XQin C(2023)Spatiotemporal Load Regulation Modeling for Internet Data Centers with Applications to Wind Power Fluctuation Suppression2023 5th Asia Energy and Electrical Engineering Symposium (AEEES)10.1109/AEEES56888.2023.10114214(1157-1163)Online publication date: 23-Mar-2023
https://doi.org/10.1109/AEEES56888.2023.10114214
Osnes IYazidi AJacobsen HEliassen FSartori S(2022)Harnessing Task Usage Prediction and Latency Sensitivity for Scheduling Workloads in Wind-Powered Data CentersEnergies10.3390/en1512446915:12(4469)Online publication date: 19-Jun-2022
https://doi.org/10.3390/en15124469
Wen ZGarg SAujla GAlwasel KPuthal DDustdar SZomaya ARanjan R(2021)Running Industrial Workflow Applications in a Software-Defined Multicloud Environment Using Green Energy Aware Scheduling AlgorithmIEEE Transactions on Industrial Informatics10.1109/TII.2020.304569017:8(5645-5656)Online publication date: Aug-2021
https://doi.org/10.1109/TII.2020.3045690
Show More Cited By

Index Terms

Utilizing green energy prediction to schedule mixed batch and service jobs in data centers
1. General and reference
  1. Cross-computing tools and techniques
    1. Performance
2. Software and its engineering
  1. Software organization and properties
    1. Contextual software domains
      1. Operating systems
        Process management
    2. Extra-functional properties
      1. Software performance

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Information & Contributors

Information

Published In

cover image ACM SIGOPS Operating Systems Review

ACM SIGOPS Operating Systems Review Volume 45, Issue 3

December 2011

94 pages

ISSN:0163-5980

DOI:10.1145/2094091

Issue’s Table of Contents

Copyright © 2012 Authors.

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 11 January 2012

Published in SIGOPS Volume 45, Issue 3

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Cited By

Liu WWei KYan XQin C(2023)Spatiotemporal Load Regulation Modeling for Internet Data Centers with Applications to Wind Power Fluctuation Suppression2023 5th Asia Energy and Electrical Engineering Symposium (AEEES)10.1109/AEEES56888.2023.10114214(1157-1163)Online publication date: 23-Mar-2023
https://doi.org/10.1109/AEEES56888.2023.10114214
Osnes IYazidi AJacobsen HEliassen FSartori S(2022)Harnessing Task Usage Prediction and Latency Sensitivity for Scheduling Workloads in Wind-Powered Data CentersEnergies10.3390/en1512446915:12(4469)Online publication date: 19-Jun-2022
https://doi.org/10.3390/en15124469
Wen ZGarg SAujla GAlwasel KPuthal DDustdar SZomaya ARanjan R(2021)Running Industrial Workflow Applications in a Software-Defined Multicloud Environment Using Green Energy Aware Scheduling AlgorithmIEEE Transactions on Industrial Informatics10.1109/TII.2020.304569017:8(5645-5656)Online publication date: Aug-2021
https://doi.org/10.1109/TII.2020.3045690
Zhao YHuang GWang GYao ZPeng CPan F(2020)Corrosion and Discharge Performance of Mg-2Zn-0.5Ce-0.5Mn-0.2Ca Alloy in NaCl SolutionInternational Journal of Electrochemical Science10.20964/2020.02.1915:2(1082-1090)Online publication date: Feb-2020
https://doi.org/10.20964/2020.02.19
Arora SBala A(2020)A survey: ICT enabled energy efficiency techniques for big data applicationsCluster Computing10.1007/s10586-019-02958-623:2(775-796)Online publication date: 1-Jun-2020
https://dl.acm.org/doi/10.1007/s10586-019-02958-6
Li YWang XLuo PPan Q(2019)Thermal-Aware Hybrid Workload Management in a Green Datacenter towards Renewable Energy UtilizationEnergies10.3390/en1208149412:8(1494)Online publication date: 19-Apr-2019
https://doi.org/10.3390/en12081494
Czarnul PProficz JKrzywaniak A(2019)Energy-Aware High-Performance ComputingScientific Programming10.1155/2019/83487912019Online publication date: 1-Jan-2019
https://dl.acm.org/doi/10.1155/2019/8348791
Malla SChristensen K(2019)A Survey on Power Management Techniques for Oversubscription of Multi-Tenant Data CentersACM Computing Surveys10.1145/329104952:1(1-31)Online publication date: 13-Feb-2019
https://dl.acm.org/doi/10.1145/3291049
Khosravi ABuyya R(2018)Energy and Carbon Footprint-Aware Management of Geo-Distributed Cloud Data CentersSustainable Development10.4018/978-1-5225-3817-2.ch064(1456-1475)Online publication date: 2018
https://doi.org/10.4018/978-1-5225-3817-2.ch064
Li DQu XWan JWang JXia YZhuang XXie C(2018)Workload Scheduling for Massive Storage Systems with Arbitrary Renewable SupplyIEEE Transactions on Parallel and Distributed Systems10.1109/TPDS.2018.282007029:10(2373-2387)Online publication date: 1-Oct-2018
https://doi.org/10.1109/TPDS.2018.2820070
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