Name
Abstract | ||
|---|---|---|
In recent years, the question of the energy consumption of data centers has become more and more important, and several studies raised the possibility of using renewable energy to power them. The intermittent nature of commonly used renewable energy sources is a major drawback of using them directly on-site. In this paper, we present an approach for scheduling batch jobs with due date constraints, which takes into account the availability of the renewable energy to reduce the need of brown energy and therefore running cost. The approach we propose differs from the existing methods by providing a scheduling algorithm agnostic of the electrical infrastructure. A separated system, managing the renewable sources, provides an arbitrary objective function, which is used to guide the scheduling heuristic. We implemented our approach in a data center simulator, and evaluated it by considering a small-scale center powered with solar panels and connected to the electrical grid. The relationship between the flexibility allowed by the user negotiated SLAs and the behavior of the algorithm is studied, and compared to existing approaches from the literature. Our experiments show a reduction of brown energy consumption up to 49% and a cost saving up to 51%, compared to a traditional scheduler unaware of renewable availability. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.future.2018.03.049 | Future Generation Computer Systems |
Keywords | Field | DocType |
Renewable energy,Online scheduling,Data center,Energy aware scheduling | Drawback,Green computing,Renewable energy,Scheduling (computing),Computer science,Batch processing,Electrical grid,Data center,Energy consumption,Distributed computing | Journal |
Volume | ISSN | Citations |
86 | 0167-739X | 5 |
PageRank | References | Authors |
0.44 | 18 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Leo Grange | 1 | 11 | 1.67 |
| G. Da Costa | 2 | 84 | 8.09 |
| Patricia Stolf | 3 | 125 | 17.37 |