Analyzing Power Decisions in Data Center Powered by Renewable Sources

Abstract

Both academics and industry have engaged their efforts in reducing greenhouse gas (GHG) emissions of Information and Communications Technology (ICT). Data centers are one of the most electricity-expensive ICT actors due to their uninterrupted service. Reducing the usage of brown energy or migrating to green energy using renewable sources (RES) is a way to reduce these emissions. However, this migration is not straightforward due to intermittence from these sources. This work is part of Datazero 2 ANR project. This project aims to design a data center powered only by RES production and storage elements. This architecture requires several decisions at different levels of management. This project divides the problem into two groups: offline and online. On the offline side, it uses renewable and workload predictions to prepare an offline plan with a power envelope (power delivered to the servers) and hints on how to manage the storage (batteries and hydrogen). Given the offline plan, the article's contribution is how to deal with real and dynamic power constraints online while keeping the planned storage level at the end. So, this article proposes policies to modify the plan according to the changes in predictions. We evaluate these policies in a homogeneous and heterogeneous data center. The results demonstrate that our policies could approach the storage level and improve Quality of Service (QoS) independently of data center infrastructures.

BEASY: Making EASY Backfilling Renewable-Only

“…This work focuses on offline decisions, using demand and production estimation. Finally, [17] proposes a mix of offline and online decisions, dealing with a renewableonly data center. Offline predicts usage and demand, creating an offline plan.…”

“…It is possible to notice that the majority of the works consider only online [7], [8], [11], [12], [15] or offline decisions [9], [10], [13], [16]. Therefore, to the best of our knowledge, only work [17] proposes a mix between offline and online decisions, for a renewable-only data center and considering battery awareness. However, this work does not estimate battery usage from jobs in future steps and proposes simplistic compensation policies.…”

“…Also, it only evaluates the information given by the offline plan, whereas BEASY uses predictions to find the best battery changes. We compare our results with the policies proposed in [17].…”

“…When there is no job to start, it waits to turn off the servers using the DPM technique [23]. Peak, Next, and Last policies are proposed by [17]. Fig.…”