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dc.contributor.authorThiam, Cheikhou
dc.contributor.authorThiam, Fatoumata
dc.date.accessioned2021-04-17T18:57:15Z
dc.date.available2021-04-17T18:57:15Z
dc.date.issued2019
dc.identifier.urihttp://52.157.139.19:8080/xmlui/handle/123456789/82
dc.descriptionConference paper presented in the 2019 Third International Conference on Intelligent Computing in Data Sciences (ICDS), Marrakech, Morocco: https://ieeexplore.ieee.org/document/8942232/en_US
dc.description.abstractThe cloud data Center uses more and more computers leading to the need for new electrical installations each year, increasing thus power consumption. Many studies on optimizing energy consumption have recently been conducted. As a result, many techniques aimed at reducing energy consumption have been adopted. Efficient VM management can reduce energy consumed. In this paper, we investigate the energy minimization problem while taking into account of VM management. We introduce an algorithm which reduces the energy consumption by decreasing the number of active PMs, while also preserves quality of service (QoS). We began with a review of the various techniques used for minimizing the energy consumed in the data center by analysing them. We propose an approach based on a virtual machine (VM) migration technique. To evaluate our approach, we used the CloudSim simulator. We finally made simulations whose results allow us to say that our approach can improve the energy gain while preserving the quality of service.en_US
dc.publisherIEEEen_US
dc.subjectOptimizing electrical energy consumption, cloud data centeren_US
dc.titleOptimizing electrical energy consumption in cloud data centeren_US
dc.typePresentationen_US
Appears in Collections:ICTs including Big Data and Artificial Intelligence

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