Studying the Energy Consumption of Stream Processing Engines in the Cloud
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| Titel: | Studying the Energy Consumption of Stream Processing Engines in the Cloud |
|---|---|
| Autoren: | KP, Govind, Pierre, Guillaume, Rouvoy, Romain |
| Weitere Verfasser: | 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 |
| Quelle: | 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 |
| Verlagsinformationen: | HAL CCSD IEEE |
| Publikationsjahr: | 2023 |
| Bestand: | Université de Rennes 1: Publications scientifiques (HAL) |
| Schlagwörter: | Green computing, Data stream processing, Energy consumption, Reproducibility, [INFO]Computer Science [cs] |
| Geographisches Schlagwort: | Boston (MA), United States |
| Time: | Boston (MA), United States |
| Beschreibung: | 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. |
| Publikationsart: | conference object |
| Sprache: | English |
| Verfügbarkeit: | 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 |
| Dokumentencode: | edsbas.B47101C8 |
| Datenbank: | BASE |
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