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

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Abstract

The advent of services such as cloud computing, social networks and e-commerce has led to an increased demand for computer resources from data centers. Prominent issues for data center designers are sustainability, cost, and dependability, which are each significantly affected by the redundant architectures required to support these services. Within this context, models are important tools for designers when attempting to quantify these issues before implementing the final architecture. This paper proposes a set of models for the integrated quantification of the sustainability impact, cost, and dependability of data center power and cooling infrastructures. This is achieved with the support of an environment called ASTRO. The approach taken to perform the system dependability evaluation employs a hybrid modeling strategy which recognizes the advantages of both stochastic Petri nets and reliability block diagrams. Additionally, an energy flow model is proposed to estimate the environmental impact and cost of data center architectures whilst respecting the energy constraints of each device. This work also presents a case study which analyzes the environmental impact and dependability metrics as well as the operational energy cost of real-world data center power and cooling architectures within the context of the energy mixes of the US and Brazil.

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Acknowledgments

The authors would like to thank the reviewers for their valuable comments and suggestions to improve the quality of this work. The authors would like to thank CNPQ for financing the project (290018/2011-0) and supporting the development of this work.

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Correspondence to Gustavo Callou.

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Callou, G., Maciel, P., Tutsch, D. et al. Estimating sustainability impact of high dependable data centers: a comparative study between Brazilian and US energy mixes. Computing 95, 1137–1170 (2013). https://doi.org/10.1007/s00607-013-0328-y

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