Joint virtual machine allocation and power portfolio optimization for data centers in smart grid environment

Generally, data centers consume a great amount of electric power which incurs the major operating cost to a data center owner. Currently, smart grid whose one of the important features is the realtime pricing will be implemented by the public utility in a near future such that the owner could also encounter a risk of fluctuating electricity prices (i.e., spot prices) in electricity spot markets. To hedge against such a risk, the owner can sign forward contracts from electricity futures markets. In this paper, a stochastic programming model is formulated to jointly optimize the power cost in the electricity markets and the operating cost of virtual machine allocation in data centers. Numerical studies are performed to evaluate the model. The results clearly show that the proposed model can significantly reduce the cost of operating data centers under uncertainties of demand and power prices.

[1]  Feng Zhao,et al.  Energy aware consolidation for cloud computing , 2008, CLUSTER 2008.

[2]  Pierluigi Siano,et al.  An overview on the smart grid concept , 2010, IECON 2010 - 36th Annual Conference on IEEE Industrial Electronics Society.

[3]  Werner Vogels,et al.  Beyond Server Consolidation , 2008, ACM Queue.

[4]  Antonio Corradi,et al.  Increasing Cloud power efficiency through consolidation techniques , 2011, 2011 IEEE Symposium on Computers and Communications (ISCC).

[5]  S. Pickle,et al.  Primer on electricity futures and other derivatives , 1998 .

[6]  Asfandyar Qureshi Plugging Into Energy Market Diversity , 2008, HotNets.

[7]  Rajkumar Buyya,et al.  Energy Efficient Resource Management in Virtualized Cloud Data Centers , 2010, 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing.

[8]  Amir-Hamed Mohsenian-Rad,et al.  Coordination of Cloud Computing and Smart Power Grids , 2010, 2010 First IEEE International Conference on Smart Grid Communications.

[9]  Julia L. Higle,et al.  Stochastic Programming: Optimization When Uncertainty Matters , 2005 .

[10]  Amir-Hamed Mohsenian-Rad,et al.  Energy-Information Transmission Tradeoff in Green Cloud Computing , 2010 .

[11]  Dmytro Dyachuk,et al.  Optimizing Cloud providers revenues via energy efficient server allocation , 2012, Sustain. Comput. Informatics Syst..

[12]  Bu-Sung Lee,et al.  Optimal Power Management for Server Farm to Support Green Computing , 2009, 2009 9th IEEE/ACM International Symposium on Cluster Computing and the Grid.