Indian Journal of Innovations and Developments

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Dynamic Optimization of VM to Server Mapping


Affiliations
1 Kathir College of engineering, Coimbatore, Tamil Nadu 641062, India
 

Background/Objectives: To dynamically optimize the Virtual machines for server mapping in the cloud environments to avoid server underutilization and overloading of the organizations utilizing virtualized data centresso that the overall power consumption and carbon emissions are minimized.

Methods/Statistical analysis: To avoid server underutilization, server consolidation plans at minimizing the number of server machines utilized in the data centres by consolidating load and improving resource utilization of physical systems. Server consolidation of virtual machines (VMs) via live migration and exchanging idle nodes to the sleep mode permit Cloud providers to improve resource usage and minimize energy consumption. Server consolidation during live migration is an effective method in the direction of energy conservation in cloud data centers. Even though a batch of research and review has been performed on server consolidation, a variety of problems involved have mainly been offered in isolation of each other. In this paper, initiate with a set of heuristic approaches for dynamic optimization of the VM-to-server mapping based on grouping of fundamental management actions, such as removing and restarting physical machines, VM migration, and removing and restarting VMs.

Findings: The proposed approach utilizes the service consolidation to avoid server underutilization and overloading to enhance the usage of several-utilized servers in data centres acquiring reduced system management cost. Thus the server is utilized efficiently in the organization with low management cost.

Improvements/Applications: Overall utilization of the datacenter is improved using our approach and the power consumption and carbon emissions are minimized.


Keywords

Cloud Computing,dynamic Optimization, Virtual Machines, Server Mapping.
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  • Dynamic Optimization of VM to Server Mapping

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Authors

B. Pavithraselvi
Kathir College of engineering, Coimbatore, Tamil Nadu 641062, India
B. Sandhya
Kathir College of engineering, Coimbatore, Tamil Nadu 641062, India

Abstract


Background/Objectives: To dynamically optimize the Virtual machines for server mapping in the cloud environments to avoid server underutilization and overloading of the organizations utilizing virtualized data centresso that the overall power consumption and carbon emissions are minimized.

Methods/Statistical analysis: To avoid server underutilization, server consolidation plans at minimizing the number of server machines utilized in the data centres by consolidating load and improving resource utilization of physical systems. Server consolidation of virtual machines (VMs) via live migration and exchanging idle nodes to the sleep mode permit Cloud providers to improve resource usage and minimize energy consumption. Server consolidation during live migration is an effective method in the direction of energy conservation in cloud data centers. Even though a batch of research and review has been performed on server consolidation, a variety of problems involved have mainly been offered in isolation of each other. In this paper, initiate with a set of heuristic approaches for dynamic optimization of the VM-to-server mapping based on grouping of fundamental management actions, such as removing and restarting physical machines, VM migration, and removing and restarting VMs.

Findings: The proposed approach utilizes the service consolidation to avoid server underutilization and overloading to enhance the usage of several-utilized servers in data centres acquiring reduced system management cost. Thus the server is utilized efficiently in the organization with low management cost.

Improvements/Applications: Overall utilization of the datacenter is improved using our approach and the power consumption and carbon emissions are minimized.


Keywords


Cloud Computing,dynamic Optimization, Virtual Machines, Server Mapping.

References