Data center availability is critical considering the explosive growth in Internet services and people's dependence on them. Furthermore, in recent years, sustainability has become important. However, data center designers have little information on the sustainability impact of data center availability architectures. In this paper, we present an approach to estimate the sustainability impact of such architectures. Availability is computed using Stochastic Petri Net (SPN) models while an exergy-based lifecycle assessment (LCA) approach is used for quantifying sustainability impact. The approach is demonstrated on real life data center power infrastructure architectures. Five different architectures are considered and initial results show that quantification of sustainability impact provides important information to a data center designer in evaluating availability architecture choices.
Interval arithmetic has been applied to model uncertainties and variabilities. An interval model is a space, family or class of models in which there are parameters represented by intervals, instead of real numbers. This paper describes the Interval Generalized Stochastic Petri Net (IGSPN) as an interval extension to the GSPN model. The IGSPN analysis takes into account the effects of variability on exponential transition rates and weights when calculating dependability measures. IGSPN analysis may be useful as a tool for decisionmaking. A Case study is presented for describing the models as well as for presenting the analysis methods.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.