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Article Dans Une Revue Journal of Cleaner Production Année : 2019

Benefit-cost model for comparing data center performance from a biomimicry perspective

Résumé

Data centers are estimated to have the fastest growing carbon footprint from across the whole information and communication technology (ICT) sector. Evaluating the performance of data centers in terms of energy efficiency and sustainability is becoming an increasingly important matter for organizations and governments (e.g., for regulation or reputation purposes). It nonetheless remains difficult to achieve such evaluation, as data centers imply to take into consideration a wide range of dimensions and stakeholders. Even though a wide range of sustainability performance indicators exist in the literature, there is still a lack of frameworks to help data center stakeholders (spanning from data center owners, governmental regulators to engineers/field operators) to evaluate and understand how a data center performs in terms of sustainable development/behavior. Our research work proposes such a framework, whose originality lies in the combination of state-of-the-art sustainability metrics with the biomimicry commandments of eco-mature system, which enables holistic sustainability assessment of data centres. From a theoretical perspective, the proposed model is designed based on a benefit-cost analysis using the Analytic Hierarchy Process (AHP) technique. This approach allows data center stakeholders for specifying their own preferences and/or expertise in the comparison process, whose practicability is demonstrated in this paper considering three data center candidates, which are respectively located in France, Germany and Sweden.
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Dates et versions

hal-02149239 , version 1 (25-10-2021)

Licence

Paternité - Pas d'utilisation commerciale

Identifiants

Citer

Sylvain Kubler, Eric Rondeau, Jean-Philippe Georges, Phoebe Lembi Mutua, Marta Chinnici. Benefit-cost model for comparing data center performance from a biomimicry perspective. Journal of Cleaner Production, 2019, 231, pp.817-834. ⟨10.1016/j.jclepro.2019.05.183⟩. ⟨hal-02149239⟩
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