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2019 | OriginalPaper | Buchkapitel

The SAGITTA Approach for Optimizing Solar Energy Consumption in Distributed Clouds with Stochastic Modeling

verfasst von : Benjamin Camus, Fanny Dufossé, Anne-Cécile Orgerie

Erschienen in: Smart Cities, Green Technologies, and Intelligent Transport Systems

Verlag: Springer International Publishing

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Abstract

Facing the urgent need to decrease data centers’ energy consumption, Cloud providers resort to on-site renewable energy production. Solar energy can thus be used to power data centers. Yet this energy production is intrinsically fluctuating over time and depending on the geographical location. In this paper, we propose a stochastic modeling for optimizing solar energy consumption in distributed clouds. Our approach, named SAGITTA (Stochastic Approach for Green consumption In disTributed daTA centers), is shown to produce a virtual machine scheduling close to the optimal algorithm in terms of energy savings and to outperform classical round-robin approaches over varying Cloud workloads and real solar energy generation traces.

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Titel: The SAGITTA Approach for Optimizing Solar Energy Consumption in Distributed Clouds with Stochastic Modeling
verfasst von: Benjamin Camus
Fanny Dufossé
Anne-Cécile Orgerie
Verlag: Springer International Publishing
Buch: Smart Cities, Green Technologies, and Intelligent Transport Systems
Print ISBN: 978-3-030-02906-7

Electronic ISBN: 978-3-030-02907-4

Copyright-Jahr: 2019
DOI: https://doi.org/10.1007/978-3-030-02907-4_3

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