Management of Virtual Machine as an Energy Conservation in Private Cloud Computing System

Akhmad Fauzi,Mohammad Idhom,Edy Mulyadi,Abdullah Fadil

doi:10.1051/matecconf/20165803008

Akhmad Fauzi, Mohammad Idhom + Show 2 more

Open Access

https://doi.org/10.1051/matecconf/20165803008

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Abstract

Cloud computing is a service model that is packaged in a base computing resources that can be accessed through the Internet on demand and placed in the data center. Data center architecture in cloud computing environments are heterogeneous and distributed, composed of a cluster of network servers with different capacity computing resources in different physical servers. The problems on the demand and availability of cloud services can be solved by fluctuating data center cloud through abstraction with virtualization technology. Virtual machine (VM) is a representation of the availability of computing resources that can be dynamically allocated and reallocated on demand. In this study the consolidation of VM as energy conservation in Private Cloud Computing Systems with the target of process optimization selection policy and migration of the VM on the procedure consolidation. VM environment cloud data center to consider hosting a type of service a particular application at the instance VM requires a different level of computing resources. The results of the use of computing resources on a VM that is not balanced in physical servers can be reduced by using a live VM migration to achieve workload balancing. A practical approach used in developing OpenStack-based cloud computing environment by integrating Cloud VM and VM Placement selection procedure using OpenStack Neat VM consolidation. Following the value of CPU Time used as a fill to get the average value in MHz CPU utilization within a specific time period. The average value of a VM’s CPU utilization in getting from the current CPU_time reduced by CPU_time from the previous data retrieval multiplied by the maximum frequency of the CPU. The calculation result is divided by the making time CPU_time when it is reduced to the previous taking time CPU_time multiplied by milliseconds.

Highlights

Cloud computing is a service model that provides convenience to the end-users and brokers
If the capacity of computing resources provided by the data center experienced a shortfall due to popular demand, the service provider will lose revenue as a result in the stay by the customer and the processes that occur in the cloud data center will have excess usage (Armbrust, et al, 2009)
Abstraction and Hypervisor API Implementation using libvirt Communication between the KVM with OpenStack Cloud bridged by a user application programming interface (API) using libvirt

Summary

Introduction

Cloud computing is a service model that provides convenience to the end-users and brokers. These services in the pack in the base of computing resources that can be accessed through the Internet on demand. The challenge is that if the capacity of the computing resources provided by the data center cloud more than the demand the service provider would suffer losses due to the overhead of operating costs and processes occurring in the data center will experience a shortage utilization (under utilization). If the capacity of computing resources provided by the data center experienced a shortfall due to popular demand, the service provider will lose revenue as a result in the stay by the customer and the processes that occur in the cloud data center will have excess usage (over utilization) (Armbrust, et al, 2009)

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