Zobrazit v EDS

Studying the Energy Consumption of Stream Processing Engines in the Cloud

Uloženo v:
Podrobná bibliografie
Název: Studying the Energy Consumption of Stream Processing Engines in the Cloud
Autoři: KP, Govind, Pierre, Guillaume, Rouvoy, Romain
Přispěvatelé: Design and Implementation of Autonomous Distributed Systems (MYRIADS), Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-SYSTÈMES LARGE ÉCHELLE (IRISA-D1), Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom Paris (IMT)-Institut Mines-Télécom Paris (IMT)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut Mines-Télécom Paris (IMT)-Institut Mines-Télécom Paris (IMT)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom Paris (IMT)-Institut Mines-Télécom Paris (IMT), Self-adaptation for distributed services and large software systems (SPIRALS), Inria Lille - Nord Europe, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), Institut universitaire de France (IUF), Ministère de l'Education nationale, de l’Enseignement supérieur et de la Recherche (M.E.N.E.S.R.), IEEE, Grid5000
Zdroj: IC2E 2023 - 11th IEEE International Conference on Cloud Engineering ; https://inria.hal.science/hal-04164074 ; IC2E 2023 - 11th IEEE International Conference on Cloud Engineering, IEEE, Sep 2023, Boston (MA), United States. pp.1-9
Informace o vydavateli: HAL CCSD
IEEE
Rok vydání: 2023
Sbírka: Université de Rennes 1: Publications scientifiques (HAL)
Témata: Green computing, Data stream processing, Energy consumption, Reproducibility, [INFO]Computer Science [cs]
Geografické téma: Boston (MA), United States
Time: Boston (MA), United States
Popis: International audience ; Reducing the energy consumption of the global IT industry requires one to understand and optimize the large software infrastructures the modern data economy relies on. Among them are the data stream processing systems that are deployed in cloud data centers by companies, such as Twitter, to process billion of events per day in real time. However, studying the energy consumption of such infrastructures is difficult because they rely on a complex virtualized software ecosystem where attributing energy consumption to individual software components is a challenge, and because the space of possible configurations is large. We present GreenFlow, a principled methodology and tool designed to automate the deployment of energy measurement experiments for data stream processing systems in cloud environments. GreenFlow is designed to deliver reproducible results while remaining flexible enough to support a wide range of experiments. We illustrate its usage and show in particular that consolidating a DSP system in the smallest number of servers that are capable of processing it is an effective way to reduce energy consumption.
Druh dokumentu: conference object
Jazyk: English
Dostupnost: https://inria.hal.science/hal-04164074
https://inria.hal.science/hal-04164074v1/document
https://inria.hal.science/hal-04164074v1/file/main.pdf
Rights: http://creativecommons.org/licenses/by/ ; info:eu-repo/semantics/OpenAccess
Přístupové číslo: edsbas.B47101C8
Databáze: BASE
FullText Text:
  Availability: 0
CustomLinks:
  – Url: https://inria.hal.science/hal-04164074#
    Name: EDS - BASE (s4221598)
    Category: fullText
    Text: View record from BASE
  – Url: https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=EBSCO&SrcAuth=EBSCO&DestApp=WOS&ServiceName=TransferToWoS&DestLinkType=GeneralSearchSummary&Func=Links&author=KP%20G
    Name: ISI
    Category: fullText
    Text: Nájsť tento článok vo Web of Science
    Icon: https://imagesrvr.epnet.com/ls/20docs.gif
    MouseOverText: Nájsť tento článok vo Web of Science
Header DbId: edsbas
DbLabel: BASE
An: edsbas.B47101C8
RelevancyScore: 954
AccessLevel: 3
PubType: Conference
PubTypeId: conference
PreciseRelevancyScore: 953.929138183594
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Studying the Energy Consumption of Stream Processing Engines in the Cloud
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22KP%2C+Govind%22">KP, Govind</searchLink><br /><searchLink fieldCode="AR" term="%22Pierre%2C+Guillaume%22">Pierre, Guillaume</searchLink><br /><searchLink fieldCode="AR" term="%22Rouvoy%2C+Romain%22">Rouvoy, Romain</searchLink>
– Name: Author
  Label: Contributors
  Group: Au
  Data: Design and Implementation of Autonomous Distributed Systems (MYRIADS)<br />Inria Rennes – Bretagne Atlantique<br />Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-SYSTÈMES LARGE ÉCHELLE (IRISA-D1)<br />Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA)<br />Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes)<br />Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique)<br />Institut Mines-Télécom Paris (IMT)-Institut Mines-Télécom Paris (IMT)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes)<br />Institut Mines-Télécom Paris (IMT)-Institut Mines-Télécom Paris (IMT)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA)<br />Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique)<br />Institut Mines-Télécom Paris (IMT)-Institut Mines-Télécom Paris (IMT)<br />Self-adaptation for distributed services and large software systems (SPIRALS)<br />Inria Lille - Nord Europe<br />Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL)<br />Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)<br />Institut universitaire de France (IUF)<br />Ministère de l'Education nationale, de l’Enseignement supérieur et de la Recherche (M.E.N.E.S.R.)<br />IEEE<br />Grid5000
– Name: TitleSource
  Label: Source
  Group: Src
  Data: IC2E 2023 - 11th IEEE International Conference on Cloud Engineering ; https://inria.hal.science/hal-04164074 ; IC2E 2023 - 11th IEEE International Conference on Cloud Engineering, IEEE, Sep 2023, Boston (MA), United States. pp.1-9
– Name: Publisher
  Label: Publisher Information
  Group: PubInfo
  Data: HAL CCSD<br />IEEE
– Name: DatePubCY
  Label: Publication Year
  Group: Date
  Data: 2023
– Name: Subset
  Label: Collection
  Group: HoldingsInfo
  Data: Université de Rennes 1: Publications scientifiques (HAL)
– Name: Subject
  Label: Subject Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Green+computing%22">Green computing</searchLink><br /><searchLink fieldCode="DE" term="%22Data+stream+processing%22">Data stream processing</searchLink><br /><searchLink fieldCode="DE" term="%22Energy+consumption%22">Energy consumption</searchLink><br /><searchLink fieldCode="DE" term="%22Reproducibility%22">Reproducibility</searchLink><br /><searchLink fieldCode="DE" term="%22[INFO]Computer+Science+[cs]%22">[INFO]Computer Science [cs]</searchLink>
– Name: Subject
  Label: Subject Geographic
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Boston+%28MA%29%22">Boston (MA)</searchLink><br /><searchLink fieldCode="DE" term="%22United+States%22">United States</searchLink>
– Name: Subject
  Label: Time
  Group: Su
  Data: Boston (MA), United States
– Name: Abstract
  Label: Description
  Group: Ab
  Data: International audience ; Reducing the energy consumption of the global IT industry requires one to understand and optimize the large software infrastructures the modern data economy relies on. Among them are the data stream processing systems that are deployed in cloud data centers by companies, such as Twitter, to process billion of events per day in real time. However, studying the energy consumption of such infrastructures is difficult because they rely on a complex virtualized software ecosystem where attributing energy consumption to individual software components is a challenge, and because the space of possible configurations is large. We present GreenFlow, a principled methodology and tool designed to automate the deployment of energy measurement experiments for data stream processing systems in cloud environments. GreenFlow is designed to deliver reproducible results while remaining flexible enough to support a wide range of experiments. We illustrate its usage and show in particular that consolidating a DSP system in the smallest number of servers that are capable of processing it is an effective way to reduce energy consumption.
– Name: TypeDocument
  Label: Document Type
  Group: TypDoc
  Data: conference object
– Name: Language
  Label: Language
  Group: Lang
  Data: English
– Name: URL
  Label: Availability
  Group: URL
  Data: https://inria.hal.science/hal-04164074<br />https://inria.hal.science/hal-04164074v1/document<br />https://inria.hal.science/hal-04164074v1/file/main.pdf
– Name: Copyright
  Label: Rights
  Group: Cpyrght
  Data: http://creativecommons.org/licenses/by/ ; info:eu-repo/semantics/OpenAccess
– Name: AN
  Label: Accession Number
  Group: ID
  Data: edsbas.B47101C8
PLink https://erproxy.cvtisr.sk/sfx/access?url=https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.B47101C8
RecordInfo BibRecord:
  BibEntity:
    Languages:
      – Text: English
    Subjects:
      – SubjectFull: Boston (MA)
        Type: general
      – SubjectFull: United States
        Type: general
      – SubjectFull: Green computing
        Type: general
      – SubjectFull: Data stream processing
        Type: general
      – SubjectFull: Energy consumption
        Type: general
      – SubjectFull: Reproducibility
        Type: general
      – SubjectFull: [INFO]Computer Science [cs]
        Type: general
    Titles:
      – TitleFull: Studying the Energy Consumption of Stream Processing Engines in the Cloud
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: KP, Govind
      – PersonEntity:
          Name:
            NameFull: Pierre, Guillaume
      – PersonEntity:
          Name:
            NameFull: Rouvoy, Romain
      – PersonEntity:
          Name:
            NameFull: Design and Implementation of Autonomous Distributed Systems (MYRIADS)
      – PersonEntity:
          Name:
            NameFull: Inria Rennes – Bretagne Atlantique
      – PersonEntity:
          Name:
            NameFull: Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-SYSTÈMES LARGE ÉCHELLE (IRISA-D1)
      – PersonEntity:
          Name:
            NameFull: Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA)
      – PersonEntity:
          Name:
            NameFull: Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes)
      – PersonEntity:
          Name:
            NameFull: Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique)
      – PersonEntity:
          Name:
            NameFull: Institut Mines-Télécom Paris (IMT)-Institut Mines-Télécom Paris (IMT)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes)
      – PersonEntity:
          Name:
            NameFull: Institut Mines-Télécom Paris (IMT)-Institut Mines-Télécom Paris (IMT)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA)
      – PersonEntity:
          Name:
            NameFull: Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique)
      – PersonEntity:
          Name:
            NameFull: Institut Mines-Télécom Paris (IMT)-Institut Mines-Télécom Paris (IMT)
      – PersonEntity:
          Name:
            NameFull: Self-adaptation for distributed services and large software systems (SPIRALS)
      – PersonEntity:
          Name:
            NameFull: Inria Lille - Nord Europe
      – PersonEntity:
          Name:
            NameFull: Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL)
      – PersonEntity:
          Name:
            NameFull: Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)
      – PersonEntity:
          Name:
            NameFull: Institut universitaire de France (IUF)
      – PersonEntity:
          Name:
            NameFull: Ministère de l'Education nationale, de l’Enseignement supérieur et de la Recherche (M.E.N.E.S.R.)
      – PersonEntity:
          Name:
            NameFull: IEEE
      – PersonEntity:
          Name:
            NameFull: Grid5000
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2023
          Identifiers:
            – Type: issn-locals
              Value: edsbas
            – Type: issn-locals
              Value: edsbas.oa
          Titles:
            – TitleFull: IC2E 2023 - 11th IEEE International Conference on Cloud Engineering ; https://inria.hal.science/hal-04164074 ; IC2E 2023 - 11th IEEE International Conference on Cloud Engineering, IEEE, Sep 2023, Boston (MA), United States. pp.1-9
              Type: main
ResultId 1