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

  • Benjamin Camus
  • Fanny Dufossé
  • Anne-Cécile OrgerieEmail author
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 921)


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.


Data centers Distributed clouds Energy efficiency Renewable energy Scheduling On/Off techniques 



This work has been supported by the Inria exploratory research project COSMIC (Coordinated Optimization of SMart grIds and Clouds).


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Benjamin Camus
    • 1
  • Fanny Dufossé
    • 2
  • Anne-Cécile Orgerie
    • 3
    Email author
  1. 1.Inria, IRISARennesFrance
  2. 2.Inria, CRIStALLilleFrance
  3. 3.CNRS, IRISARennesFrance

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