<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Achieving energy-efficiency with minimal Service Level Agreement (SLA) violation constraint is a major challenge in cloud datacenters owing to financial and environmental concerns. The static consolidation of Virtual Machines (VMs) is not much significant in recent time and has become outdated because of the unpredicted workload of cloud users. In this paper, a dynamic consolidation plan is proposed to optimize the energy consumption of the cloud datacenter. The proposed plan encompasses algorithms for VM selection and VM placement. The VM selection algorithm estimates power consumption of each VM to select the required VMs for migration from the overloaded Physical Machine (PM). The proposed VM allocation algorithm estimates the net increase in Imbalance Utilization Value (IUV) and power consumption of a PM, in advance before allocating the VM. The analysis of simulation results suggests that the proposed dynamic consolidation plan outperforms other state of arts.</p>
</abstract>

Achieving energy-efficiency with minimal Service Level Agreement (SLA) violation constraint is a major challenge in cloud datacenters owing to financial and environmental concerns. The static consolidation of Virtual Machines (VMs) is not much significant in recent time and has become outdated because of the unpredicted workload of cloud users. In this paper, a dynamic consolidation plan is proposed to optimize the energy consumption of the cloud datacenter. The proposed plan encompasses algorithms for VM selection and VM placement. The VM selection algorithm estimates power consumption of each VM to select the required VMs for migration from the overloaded Physical Machine (PM). The proposed VM allocation algorithm estimates the net increase in Imbalance Utilization Value (IUV) and power consumption of a PM, in advance before allocating the VM. The analysis of simulation results suggests that the proposed dynamic consolidation plan outperforms other state of arts.

VM Consolidation Plan for Improving the Energy Efficiency of Cloud

Department of Computer Science, Gurukula Kangri Vishwavidyalaya

Cybernetics and Information Technologies

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

{"article-title":"VM Consolidation Plan for Improving the Energy Efficiency of Cloud"}

Achieving energy-efficiency with minimal Service Level Agreement (SLA) violation constraint is a major challenge in cloud datacenters owing to financial and...

VM Consolidation Plan for Improving the Energy Efficiency of Cloud

Online veröffentlicht: 07. Dez. 2021

Seitenbereich: 145 - 159

Eingereicht: 18. Jan. 2021

Akzeptiert: 10. Aug. 2021

DOI: https://doi.org/10.2478/cait-2021-0035

Schlüsselwörter
VM consolidation, VM selection, VM allocation, resource allocation, power consumption, energy efficiency

© 2021 Satveer et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

VM Consolidation Plan for Improving the Energy Efficiency of Cloud

Online veröffentlicht: 07. Dez. 2021

Seitenbereich: 145 - 159

Eingereicht: 18. Jan. 2021

Akzeptiert: 10. Aug. 2021

DOI: https://doi.org/10.2478/cait-2021-0035

SchlüsselwörterVM consolidation, VM selection, VM allocation, resource allocation, power consumption, energy efficiency

© 2021 Satveer et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Schlüsselwörter
VM consolidation, VM selection, VM allocation, resource allocation, power consumption, energy efficiency