PLDAD—An Algorihm to Reduce Data Center Energy Consumption

PLDAD—An Algorihm to Reduce Data Center Energy Consumption

Due to the demands of new technologies such as social networks, e-commerce and cloud computing, more energy is being consumed in order to store all the produced data. While these new technologies require high levels of availability, a reduction in the cost and environmental impact is also expected....

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Bibliographic Details
Main Authors: Joao Ferreira, Gustavo Callou, Dietmar Tutsch, Paulo Maciel
Format: Article
Language:English
Published: MDPI AG 2018-10-01
Series:Energies
Subjects:
energy flow model
dependability
sustainability
data center
power architectures
optimization
Online Access:http://www.mdpi.com/1996-1073/11/10/2821
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spelling doaj-2d8a88ce1e9e4ebbb2fbb671fb2fadd82020-11-24T21:43:14ZengMDPI AGEnergies1996-10732018-10-011110282110.3390/en11102821en11102821PLDAD—An Algorihm to Reduce Data Center Energy ConsumptionJoao Ferreira0Gustavo Callou1Dietmar Tutsch2Paulo Maciel3Informatics Center, Federal University of Pernambuco, Recife 50740-560, BrazilDepartament of Computing, Federal Rural University of Pernambuco, Recife 52171-900, BrazilAutomation Technologye, Bergische Universität Wuppertal, D-42119 Wuppertal, GermanyInformatics Center, Federal University of Pernambuco, Recife 50740-560, BrazilDue to the demands of new technologies such as social networks, e-commerce and cloud computing, more energy is being consumed in order to store all the produced data. While these new technologies require high levels of availability, a reduction in the cost and environmental impact is also expected. The present paper proposes a power balancing algorithm (power load distribution algorithm-depth (PLDA-D)) to optimize the energy distribution of data center electrical infrastructures. The PLDA-D is based on the Bellman and Ford–Fulkerson flow algorithms that analyze energy-flow models (EFM). EFM computes the power efficiency, sustainability and cost metrics of data center infrastructures. To demonstrate the applicability of the proposed strategy, we present a case study that analyzes four power infrastructures. The results obtained show about a 3.8% reduction in sustainability impact and operational costs.http://www.mdpi.com/1996-1073/11/10/2821energy flow modeldependabilitysustainabilitydata centerpower architecturesoptimization
collection DOAJ
language English
format Article
sources DOAJ
author Joao Ferreira
Gustavo Callou
Dietmar Tutsch
Paulo Maciel
spellingShingle Joao Ferreira
Gustavo Callou
Dietmar Tutsch
Paulo Maciel
PLDAD—An Algorihm to Reduce Data Center Energy Consumption
Energies
energy flow model
dependability
sustainability
data center
power architectures
optimization
author_facet Joao Ferreira
Gustavo Callou
Dietmar Tutsch
Paulo Maciel
author_sort Joao Ferreira
title PLDAD—An Algorihm to Reduce Data Center Energy Consumption
title_short PLDAD—An Algorihm to Reduce Data Center Energy Consumption
title_full PLDAD—An Algorihm to Reduce Data Center Energy Consumption
title_fullStr PLDAD—An Algorihm to Reduce Data Center Energy Consumption
title_full_unstemmed PLDAD—An Algorihm to Reduce Data Center Energy Consumption
title_sort pldad—an algorihm to reduce data center energy consumption
publisher MDPI AG
series Energies
issn 1996-1073
publishDate 2018-10-01
description Due to the demands of new technologies such as social networks, e-commerce and cloud computing, more energy is being consumed in order to store all the produced data. While these new technologies require high levels of availability, a reduction in the cost and environmental impact is also expected. The present paper proposes a power balancing algorithm (power load distribution algorithm-depth (PLDA-D)) to optimize the energy distribution of data center electrical infrastructures. The PLDA-D is based on the Bellman and Ford–Fulkerson flow algorithms that analyze energy-flow models (EFM). EFM computes the power efficiency, sustainability and cost metrics of data center infrastructures. To demonstrate the applicability of the proposed strategy, we present a case study that analyzes four power infrastructures. The results obtained show about a 3.8% reduction in sustainability impact and operational costs.
topic energy flow model
dependability
sustainability
data center
power architectures
optimization
url http://www.mdpi.com/1996-1073/11/10/2821
work_keys_str_mv AT joaoferreira pldadanalgorihmtoreducedatacenterenergyconsumption
AT gustavocallou pldadanalgorihmtoreducedatacenterenergyconsumption
AT dietmartutsch pldadanalgorihmtoreducedatacenterenergyconsumption
AT paulomaciel pldadanalgorihmtoreducedatacenterenergyconsumption
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