A Formal Approach to the Quantification of Sustainability and Dependability Metrics on Data Center Infrastructures

Gustavo Callou, Erica Sousa, Paulo Maciel, Eduardo Tavares, Bruno Silva, Jair Figueirêdo, Carlos Araujo, Fabio Magnani and Francisco Neves

Symposium On Theory of Modeling and Simulation - DEVS Integrative M&S Symposium (TMS/DEVS 2011)
Boston, MA, USA, April 4-9, 2011

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Summary

Sustainability has received great attention by the scientific community, due to concerns for meeting current needs of energy without compromising, for instance, non-renewable resources for future generations. In addition, as a result of stringent availability constraints, dependability plays an prominent role in the infrastructure that supports business service through the Internet, particularly, the growth of cloud computing paradigm. In this context, tools are important to support data center designers to estimate the environmental impact, dependability as well as the cost associated to the infrastructure before implementing it. This paper presents a methodology for estimating sustainability impact and dependability metrics, supported by an integrated environment, namely, ASTRO, which considers the advantage of both Reliability Block Diagrams (RBD) and Stochastic Petri Nets (SPN). ASTRO has been developed to evaluate data center infrastructures, but the environment is generic enough to evaluate general systems. Besides, real-world case studies considering 5 different data center power infrastructures are provided to demonstrate the applicability of the proposed methodology as well as the environment.

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