DocumentCode :
677783
Title :
An Algorithm to Optimize Electrical Flows
Author :
Ferreira, J. A. ; Callou, Gustavo ; Dantas, Jamilson ; Souza, Richard ; Maciel, Paulo
Author_Institution :
Inf. Center, Fed. Univ. of Pernambuco, Recife, Brazil
fYear :
2013
fDate :
13-16 Oct. 2013
Firstpage :
109
Lastpage :
114
Abstract :
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.
Keywords :
load flow; optimisation; power consumption; power supplies to apparatus; cloud computing; cloud infrastructure; electric energy consumption; electrical flows; energy flow model; power load distribution algorithm; private cloud power architectures; Availability; Cloud computing; Computational modeling; Computer architecture; Energy consumption; Load modeling; ASTRO/Mercury; cloud power architectures; dependability; energy flow model; optimization; power load distribution algorithm; sustainability;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems, Man, and Cybernetics (SMC), 2013 IEEE International Conference on
Conference_Location :
Manchester
Type :
conf
DOI :
10.1109/SMC.2013.26
Filename :
6721779
Link To Document :
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