Socially-responsible load scheduling algorithms for sustainable data centers over smart grid
Power consumption of data centers accounts for a significant portion of operational cost for service providers. However, it is not sufficient to minimize electricity cost only. Instead, service providers should also consider the sustainability of data centers. In this paper, we investigate the probl...
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sg-ntu-dr.10356-964832020-05-28T07:19:07Z Socially-responsible load scheduling algorithms for sustainable data centers over smart grid He, Jian Deng, Xiang Wu, Dan Wen, Yonggang Wu, Di School of Computer Engineering IEEE International Conference on Smart Grid Communications (3rd : 2012 : Tainan, Taiwan) DRNTU::Engineering::Computer science and engineering Power consumption of data centers accounts for a significant portion of operational cost for service providers. However, it is not sufficient to minimize electricity cost only. Instead, service providers should also consider the sustainability of data centers. In this paper, we investigate the problem of socially-responsible load scheduling for sustainable data centers in a smart grid environment. We formulate the joint optimization of electricity cost, performance cost and social cost into a min-cost network flow model, which takes the diversity of regional electricity prices, user request latency, usage of renewable energy into account. We further propose both offline and online load scheduling algorithms to achieve the optimality of the objective cost function. Finally, a series of simulation experiments are conducted to evaluate the effectiveness of our proposed algorithms. 2013-07-22T04:39:00Z 2019-12-06T19:31:19Z 2013-07-22T04:39:00Z 2019-12-06T19:31:19Z 2012 2012 Conference Paper He, J., Deng, X., Wu, D., Wen, Y., & Wu, D. (2012). Socially-responsible load scheduling algorithms for sustainable data centers over smart grid. 2012 IEEE Third International Conference on Smart Grid Communications (SmartGridComm). https://hdl.handle.net/10356/96483 http://hdl.handle.net/10220/11967 10.1109/SmartGridComm.2012.6486018 en © 2012 IEEE. |
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DRNTU::Engineering::Computer science and engineering He, Jian Deng, Xiang Wu, Dan Wen, Yonggang Wu, Di Socially-responsible load scheduling algorithms for sustainable data centers over smart grid |
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Power consumption of data centers accounts for a significant portion of operational cost for service providers. However, it is not sufficient to minimize electricity cost only. Instead, service providers should also consider the sustainability of data centers. In this paper, we investigate the problem of socially-responsible load scheduling for sustainable data centers in a smart grid environment. We formulate the joint optimization of electricity cost, performance cost and social cost into a min-cost network flow model, which takes the diversity of regional electricity prices, user request latency, usage of renewable energy into account. We further propose both offline and online load scheduling algorithms to achieve the optimality of the objective cost function. Finally, a series of simulation experiments are conducted to evaluate the effectiveness of our proposed algorithms. |
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School of Computer Engineering |
author_facet |
School of Computer Engineering He, Jian Deng, Xiang Wu, Dan Wen, Yonggang Wu, Di |
format |
Conference or Workshop Item |
author |
He, Jian Deng, Xiang Wu, Dan Wen, Yonggang Wu, Di |
author_sort |
He, Jian |
title |
Socially-responsible load scheduling algorithms for sustainable data centers over smart grid |
title_short |
Socially-responsible load scheduling algorithms for sustainable data centers over smart grid |
title_full |
Socially-responsible load scheduling algorithms for sustainable data centers over smart grid |
title_fullStr |
Socially-responsible load scheduling algorithms for sustainable data centers over smart grid |
title_full_unstemmed |
Socially-responsible load scheduling algorithms for sustainable data centers over smart grid |
title_sort |
socially-responsible load scheduling algorithms for sustainable data centers over smart grid |
publishDate |
2013 |
url |
https://hdl.handle.net/10356/96483 http://hdl.handle.net/10220/11967 |
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1681059226863009792 |