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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Acknowledgments
This work has been supported by the Inria exploratory research project COSMIC (Coordinated Optimization of SMart grIds and Clouds).
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Camus, B., Dufossé, F., Orgerie, AC. (2019). The SAGITTA Approach for Optimizing Solar Energy Consumption in Distributed Clouds with Stochastic Modeling. In: Donnellan, B., Klein, C., Helfert, M., Gusikhin, O., Pascoal, A. (eds) Smart Cities, Green Technologies, and Intelligent Transport Systems. SMARTGREENS VEHITS 2017 2017. Communications in Computer and Information Science, vol 921. Springer, Cham. https://doi.org/10.1007/978-3-030-02907-4_3
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