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An Algorithm to Optimize Electrical Flows
| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Ferreira, Joao Callou, Gustavo Dantas, Jamilson Souza, Rafael Maciel, Paulo |
| Copyright Year | 2013 |
| Description | Cloud computing has expanded in recent years due to many effects, such as accessibility, reliability, and collaboration. To provide those functionalities high availability is in demand, which implies a higher electric energy consumption by the computers that support the cloud infrastructure. Studies that pay attention to this electric energy consumption are important due to its impact on sustainability and operational costs. This paper proposes a power load distribution algorithm (PLDA) to optimize electrical flows of power infrastructures. The PLDA adopts the Energy Flow Model (EFM) as its basis. The EFM is a model that computes sustainability impacts and cost issues, while it respects the energy providing restrictions of each component. In addition, a case study illustrates the applicability of the proposed PLDA through the analysis of six private cloud power architectures. Considerable results were observed, including a reduction on energy consumption of 10.7%, and an improvement (reduction) on the environmental impact of over 140% was obtained. |
| Starting Page | 109 |
| Ending Page | 114 |
| File Size | 351970 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781479906529 |
| DOI | 10.1109/SMC.2013.26 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2013-10-13 |
| Publisher Place | United Kingdom |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | optimization ASTRO/Mercury energy flow model dependability sustainability cloud power architectures power load distribution algorithm |
| Content Type | Text |
| Resource Type | Article |
