The rise in the penetration of the internet across the world has led to a rapid increase in the consumption of energy at the data centers established by leading cloud data service providers. High power consumption by these data centers [DCs] leads to high operational costs and high carbon emissions into the environment. From a sustainability point of view, the ultimate goal is to maximize the productivity and efficiency of these data centers while keeping greenhouse gas emissions to the minimum and maximize data center productivity. This goal can be achieved by better resource utilization and replacing carbon-intensive approaches of energy production with green sources of energy. Due to the limited intermittent availability of renewable sources of energy, the ideal ‘Green’ design for the DCs, should incorporate inter-operability with both renewable and non-renewable sources of energy. In this paper, we propose a ren-aware scheduler to schedule computational workload by prioritizing their execution within the duration of green energy availability on the basis of the predicted hourly green energy and workload data of DCs. Our results demonstrate that our ren-aware scheduler can increase the green energy consumption by 51% compared to the conventional randomized scheduler that distributes load without considering green energy and load. It can also reduce the total energy consumption by 25% by putting the DCs to sleep during their idle time, as it saves 4.5 times more idle energy than the randomized scheduler. Additionally, the results also demonstrate how the role of time zones of the DCs and the duration of green energy availability in them is pivotal in our ren-aware scheduler's performance.

互联网在全球范围内的普及率上升，导致领先的云数据服务提供商建立的数据中心的能源消耗迅速增加。这些数据中心 [DC] 的高功耗导致高运营成本和高碳排放到环境中。从可持续性的角度来看，最终目标是最大限度地提高这些数据中心的生产力和效率，同时将温室气体排放量降至最低并最大限度地提高数据中心的生产力。这一目标可以通过更好地利用资源和用绿色能源取代碳密集型能源生产方法来实现。由于可再生能源的间歇性可用性有限，DC 的理想“绿色”设计，应包括与可再生和不可再生能源的互操作性。在本文中，我们提出了一种 ren-aware 调度程序，通过根据预测的每小时绿色能源和 DC 的工作负载数据，在绿色能源可用性持续时间内优先执行计算工作负载来调度计算工作负载。我们的结果表明，与不考虑绿色能源和负载的传统随机调度程序相比，我们的 ren-aware 调度程序可以将绿色能源消耗增加 51%。它还可以通过让 DC 在其空闲时间进入睡眠状态将总能耗降低 25%，因为它比随机调度程序节省了 4.5 倍的空闲能量。此外，