Energy policies for data-center monolithic schedulers
Cloud computing and data centers that support this paradigm are rapidly evolving in order to satisfy new demands. These ever-growing needs represent an energy-related challenge to achieve sustainability and cost reduction. In this paper, we define an expert and intelligent system that applies variou...
| Authors: | , , |
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| Format: | article |
| Status: | Published version |
| Publication Date: | 2018 |
| Country: | España |
| Institution: | Universidad de Sevilla (US) |
| Repository: | idUS. Depósito de Investigación de la Universidad de Sevilla |
| OAI Identifier: | oai:idus.us.es:11441/130703 |
| Online Access: | https://hdl.handle.net/11441/130703 https://doi.org/10.1016/j.eswa.2018.06.007 |
| Access Level: | Open access |
| Keyword: | Energy policies Efficiency Data centre Simulation software Decision Making |
| Summary: | Cloud computing and data centers that support this paradigm are rapidly evolving in order to satisfy new demands. These ever-growing needs represent an energy-related challenge to achieve sustainability and cost reduction. In this paper, we define an expert and intelligent system that applies various en ergy policies. These policies are employed to maximize the energy-efficiency of data-center resources by simulating a realistic environment and heterogeneous workload in a trustworthy tool. An environmental and economic impact of around 20% of energy consumption can be saved in high-utilization scenarios without exerting any noticeable impact on data-center performance if an adequate policy is applied. |
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