Abstract
In the context of cloud computing, the energy consumed by the data center is higher because it contains a large number of physical machines, which in turn contain a number of virtual machines resulting in high power consumption. In addition, the cloud provider must provide a high quality of service (QoS) to its customers on the condition of not consuming a large amount of energy. Among the techniques of minimizing energy consumption is to turn down servers when the workload is low and relocate its virtual machines to another server. In this paper, we propose to combine this technique with another that uses a threshold ensuring the condition of not crossing a given level of use capacity of each server. We validate our model by numerical evaluation which demonstrates the effectiveness of the proposition in terms of energy efficiency and QoS improvement.
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Ouammou, A., Hanini, M., El Kafhali, S., Ben Tahar, A. (2018). Energy Consumption and Cost Analysis for Data Centers with Workload Control. In: Abraham, A., Haqiq, A., Muda, A., Gandhi, N. (eds) Innovations in Bio-Inspired Computing and Applications. IBICA 2017. Advances in Intelligent Systems and Computing, vol 735. Springer, Cham. https://doi.org/10.1007/978-3-319-76354-5_9
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DOI: https://doi.org/10.1007/978-3-319-76354-5_9
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