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Energy-proportional Profiling and Accounting in Heterogeneous Virtualized Environments

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Title: Energy-proportional Profiling and Accounting in Heterogeneous Virtualized Environments
Authors: Kurpicz, Mascha, Orgerie, Anne-Cécile, Sobe, Anita, Felber, Pascal
Contributors: Institut d'Informatique Neuchâtel (IIUN), Université de Neuchâtel = University of Neuchatel (UNINE), 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), Grid'5000
Source: ISSN: 2210-5379.
Publisher Information: HAL CCSD
Elsevier
Publication Year: 2018
Collection: Université de Rennes 1: Publications scientifiques (HAL)
Subject Terms: Heterogeneous Environments, Energy Estimation, Energy-awareness, Heterogeneous Environments * Corresponding Author: Anne-Cécile Orgerie, Virtualized Systems, Accounting, [INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI], [INFO.INFO-DC]Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC]
Description: International audience ; The costs of current data centers are mostly driven by their energy consumption (specifically by the air conditioning, computing and networking infrastructure). Yet, current pricing models are usually static and rarely consider the facili-ties' energy consumption per user. The challenge is to provide a fair and predictable model to attribute the overall energy costs per virtual machine (VM) in heterogeneous environments. In this paper we introduce EPAVE, a model for E nergy-P roportional Accounting in V M-based E nvironments. EPAVE allows transparent, reproducible and predictive cost calculation for users and for Cloud providers. It provides a full-cost model that does not account only for the dynamic energy consumption of a given VM, but also includes the proportional static cost of using a Cloud infrastructure. It comes with PowerIndex, a profiling and estimation model, which is able to profile the energy cost of a VM on a given server architecture and can then estimate its energy cost on a different one. We provide performance results of PowerIndex on real hardware, and we discuss the use cases and applicability of EPAVE.
Document Type: article in journal/newspaper
Language: English
DOI: 10.1016/j.suscom.2017.11.002
Availability: https://hal.science/hal-01633435
https://hal.science/hal-01633435v2/document
https://hal.science/hal-01633435v2/file/paper.pdf
https://doi.org/10.1016/j.suscom.2017.11.002
Rights: info:eu-repo/semantics/OpenAccess
Accession Number: edsbas.5937589B
Database: BASE
Description
Abstract:International audience ; The costs of current data centers are mostly driven by their energy consumption (specifically by the air conditioning, computing and networking infrastructure). Yet, current pricing models are usually static and rarely consider the facili-ties' energy consumption per user. The challenge is to provide a fair and predictable model to attribute the overall energy costs per virtual machine (VM) in heterogeneous environments. In this paper we introduce EPAVE, a model for E nergy-P roportional Accounting in V M-based E nvironments. EPAVE allows transparent, reproducible and predictive cost calculation for users and for Cloud providers. It provides a full-cost model that does not account only for the dynamic energy consumption of a given VM, but also includes the proportional static cost of using a Cloud infrastructure. It comes with PowerIndex, a profiling and estimation model, which is able to profile the energy cost of a VM on a given server architecture and can then estimate its energy cost on a different one. We provide performance results of PowerIndex on real hardware, and we discuss the use cases and applicability of EPAVE.
DOI:10.1016/j.suscom.2017.11.002