Please use this identifier to cite or link to this item: https://repository.rsif-paset.org/xmlui/handle/123456789/99
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dc.contributor.authorThiam, Cheikhou-
dc.contributor.authorThiam, Fatoumata-
dc.date.accessioned2021-07-08T05:53:27Z-
dc.date.available2021-07-08T05:53:27Z-
dc.date.issued2020-07-07-
dc.identifier.urihttps://repository.rsif-paset.org/xmlui/handle/123456789/99-
dc.descriptionConference paper presented at the 2019 IEEE AFRICON, Accra, Ghana: https://ieeexplore.ieee.org/document/9133776en_US
dc.description.abstractNowadays more attention focuses on VM management strategies in a variety of scenarios. The problem of virtual machine placement and migration is an optimization problem aiming for multiple goals. The efficiency of a data center, therefore, depends a lot on how virtual machines are provisioned and where they are located. An efficient VM allocation policy will improve energy efficiency while limiting the degradation of the quality of service (QoS) and alleviate hotspots., but will also reduce the operating costs of the data center. Migrating VMs into a fewer number of Physical Machines (PMs) can maximize the utilization of Cloud servers and reduce the energy consumption of the Cloud data center. In this paper, we study the problem of optimal VM allocation policy and migration to minimize power consumption in a data center while preserving QoS. CloudSim simulator is used to create a cloud environment. It provides the interface to deal with the physical and virtual machines. We evaluate and compare our algorithms corresponding to different approaches in order to find the one that optimizes VM placement and migration. The simulation result shows that virtual machine placement and migration techniques minimize the energy consumption, migrations and total simulation time. Nowadays more attention focuses on VM management strategies in a variety of scenarios. The problem of virtual machine placement and migration is an optimization problem aiming for multiple goals. The efficiency of a data center, therefore, depends a lot on how virtual machines are provisioned and where they are located. An efficient VM allocation policy will improve energy efficiency while limiting the degradation of the quality of service (QoS) and alleviate hotspots., but will also reduce the operating costs of the data center. Migrating VMs into a fewer number of Physical Machines (PMs) can maximize the utilization of Cloud servers and reduce the energy consumption of the Cloud data center. In this paper, we study the problem of optimal VM allocation policy and migration to minimize power consumption in a data center while preserving QoS. CloudSim simulator is used to create a cloud environment. It provides the interface to deal with the physical and virtual machines. We evaluate and compare our algorithms corresponding to different approaches in order to find the one that optimizes VM placement and migration. The simulation result shows that virtual machine placement and migration techniques minimize the energy consumption, migrations and total simulation time.en_US
dc.publisherIEEEen_US
dc.subjectEnergy, Heuristic, Virtual Machines, Cloud, Migrationen_US
dc.titleAn Energy-Efficient VM migrations optimization in Cloud Data Centersen_US
dc.typePresentationen_US
Appears in Collections:ICTs including Big Data and Artificial Intelligence

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