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<p>Nowadays, sustainability and energy considerations are becoming important concerns in mitigating the destructive effects of high energy consumption on the environment. In the realm of big data era, large-scale data processing systems are considered critical energy-consumption sources that exert significant impacts on the ecosystem. With the emergence of big data environments, which lead to the production of multi-structured data, numerous solutions and technologies have arisen to efficiently process vast amounts. Recently, a centralized data repository platform called <i>Data Lake</i> has been proposed to manage the heterogeneous data originating from diverse sources. Sustainability issues in such data management systems have received significant attention. In the dynamic environment of big data, the risk of unpredictable workloads and excessive energy usage at various phases of the data lifecycle within the data lake emphasizes the critical need for sustainable strategies. These measures aim to minimize the adverse effects of the high energy consumption during the data management procedure. In this article, we intend to design and analyze an energy-aware strategy for a green data lake framework. This strategy prioritizes ecological concerns, particularly energy consumption, by ensuring the maintenance of sufficient quality of service in terms of data availability. We present a model based on a continuous-time Markov chain (CTMC) to analyze the trade-off between energy efficiency and performance of a green data lake platform.</p>

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Toward green data lake management and analysis through a CTMC model

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年5月25日

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  • Marzieh Derakhshannia,
  • Julien Grange,
  • Nihal Pekergin

摘要

Nowadays, sustainability and energy considerations are becoming important concerns in mitigating the destructive effects of high energy consumption on the environment. In the realm of big data era, large-scale data processing systems are considered critical energy-consumption sources that exert significant impacts on the ecosystem. With the emergence of big data environments, which lead to the production of multi-structured data, numerous solutions and technologies have arisen to efficiently process vast amounts. Recently, a centralized data repository platform called Data Lake has been proposed to manage the heterogeneous data originating from diverse sources. Sustainability issues in such data management systems have received significant attention. In the dynamic environment of big data, the risk of unpredictable workloads and excessive energy usage at various phases of the data lifecycle within the data lake emphasizes the critical need for sustainable strategies. These measures aim to minimize the adverse effects of the high energy consumption during the data management procedure. In this article, we intend to design and analyze an energy-aware strategy for a green data lake framework. This strategy prioritizes ecological concerns, particularly energy consumption, by ensuring the maintenance of sufficient quality of service in terms of data availability. We present a model based on a continuous-time Markov chain (CTMC) to analyze the trade-off between energy efficiency and performance of a green data lake platform.