Estimating sustainability impact of high dependable data centers: a comparative study between Brazilian and US energy mixes

Callou, Gustavo; Maciel, Paulo; Tutsch, Dietmar; Ferreira, Joao; Araújo, Julian; Souza, Rafael Borim de

doi:10.1007/s00607-013-0328-y

Cited by 29 publications

(29 citation statements)

References 14 publications

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“…Many current researchers are focused on reducing energy consumption (e.g., [5] [6] [7]), which is highly relevant to IT companies. These studies usually focus on minimizing the operational cost and the sustainability impact.…”

Section: Introductionmentioning

confidence: 99%

An Algorithm to Optimize Electrical Flows

Ferreira

Callou

Dantas

et al. 2013

2013 IEEE International Conference on Systems, Man, and Cybernetics

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Cloud computing has expanded in recent years due to many effects, such as accessibility, reliability, and collaboration. To provide those functionalities high availability is in demand, which implies a higher electric energy consumption by the computers that support the cloud infrastructure. Studies that pay attention to this electric energy consumption are important due to its impact on sustainability and operational costs. This paper proposes a power load distribution algorithm (PLDA) to optimize electrical flows of power infrastructures. The PLDA adopts the Energy Flow Model (EFM) as its basis. The EFM is a model that computes sustainability impacts and cost issues, while it respects the energy providing restrictions of each component. In addition, a case study illustrates the applicability of the proposed PLDA through the analysis of six private cloud power architectures. Considerable results were observed, including a reduction on energy consumption of 10.7%, and an improvement (reduction) on the environmental impact of over 140% was obtained.

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Section: Introductionmentioning

confidence: 99%

An Algorithm to Optimize Electrical Flows

Ferreira

Callou

Dantas

et al. 2013

2013 IEEE International Conference on Systems, Man, and Cybernetics

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“…However, authors do not assess the impact of UPS system in service availability. In [8], authors presented models to evaluate the impact, cost, and dependability of data center cooling and power infrastructures. RBD and SPN was used to model different architectures.…”

Section: Related Workmentioning

confidence: 99%

How to Improve Cloud Services Availability? Investigating the Impact of Power and It Subsystems Failures

Rosendo

Leoni

Gomes

et al. 2018

Proceedings of the 51st Hawaii International Conference on System Sciences

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The cloud data center is a complex system composed of power, cooling, and IT subsystems. The power subsystem is crucial to feed the IT equipment. Power disruptions may result in service unavailability. This paper analyzes the impact of the power subsystem failures on IT services regarding different architecture configurations based on TIA-942 standard such as non-redundant, redundant, concurrently maintainable, and fault tolerant. We model both subsystems, power and IT, through Stochastic Petri Net (SPN). The availability results show that a fault tolerant power and IT configuration reduces the downtime from 54.1 to 34.5 hours/year when compared to a nonredundant architecture. The sensibility analysis results show that the failure and repair rates of the server component in a fault tolerant system present the highest impact on overall data center availability.

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“…Additionally, the dependability, cost and sustainability issues are computed through the Energy Flow Model (EFM) and Reliability Block Diagrams (RBD)/Stochastic Petri Nets (SPN) models supported by the ASTRO environment [16]. This paper extends our previous work [6,17] in which an integrated approach for computing sustainability, dependability and cost issues is proposed. The main goal in this current paper is to improve the electrical energy flow of EFM models and, as a result, improve the metrics obtained through that model.…”

Section: Introductionmentioning

confidence: 77%

“…Algorithms are employed to traverse the EFM in order to compute the energy consumption, sustainability impact and the operational cost of data center architectures [17]. This work proposes a new algorithm to optimize the energy flow between components by taking into account the electrical efficiency of the devices present in the EFM models.…”

Section: Introductionmentioning

confidence: 99%

A Power Load Distribution Algorithm to Optimize Data Center Electrical Flow

2013

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Energy consumption is a matter of common concern in the world today. Research demonstrates that as a consequence of the constantly evolving and expanding field of information technology, data centers are now major consumers of electrical energy. Such high electrical energy consumption emphasizes the issues of sustainability and cost. Against this background, the present paper proposes a power load distribution algorithm (PLDA) to optimize energy distribution of data center power infrastructures. The PLDA, which is based on the Ford-Fulkerson algorithm, is supported by an environment called ASTRO, capable of performing the integrated evaluation of dependability, cost and sustainability. More specifically, the PLDA optimizes the flow distribution of the energy flow model (EFM). EFMs are responsible for estimating sustainability and cost issues of data center infrastructures without crossing the restrictions of the power capacity that each device can provide (power system) or extract (cooling system). Additionally, a case study is presented that analyzed seven data center power architectures. Significant results were observed, achieving a reduction in power consumption of up to 15.5%.

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Estimating sustainability impact of high dependable data centers: a comparative study between Brazilian and US energy mixes

Cited by 29 publications

References 14 publications

An Algorithm to Optimize Electrical Flows

An Algorithm to Optimize Electrical Flows

How to Improve Cloud Services Availability? Investigating the Impact of Power and It Subsystems Failures

A Power Load Distribution Algorithm to Optimize Data Center Electrical Flow

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