Power and Resource-Aware Virtual Machine Placement for IaaS Cloud
Abstract
Cloud computing is a pool of abundant computing resources and delivers Internet-based computing services on demand. One of the challenging issues in virtualization is placing virtual machines (VMs) on physical machines (PMs) so that the computing resources can be used efficiently. Power and resource-aware virtual machine placement for IaaS cloud In addition, imbalanced use of multi-dimensional resources can lead to a cloud data center’s overall resource wastage and SLA violations.
In this paper, we propose a new VM placement algorithm called multi-objective virtual machine placement (MOVMP) for IaaS cloud. In the algorithm Power and resource-aware virtual machine placement for IaaS cloud , we devise a resource usage factor (RUF) to maximize the resource usage of the PMs during placement of the VMs. Further, we also present a multi-dimensional resource usage model, which direct to minimize the number of under-loaded PMs in IaaS cloud. This model also helps to improve resource utilization in a balanced manner and migrate a less number of VMs, which results in minimizing the resource wastage, power consumption, and the service level agreement (SLA) violations of cloud data center. The algorithm is tested using Amazon EC2 Instances.
System Configuration
H/W System Configuration
Speed : 1.1 GHz
RAM : 256 MB(min)
Hard Disk : 20 GB
Floppy Drive : 1.44 MB
Key Board : Standard Windows Keyboard
Mouse : Two or Three Button Mouse
Monitor : SVGA
S/W System Configuration
Platform : cloud computing
Operating system : Windows Xp,7,
Server : WAMP/Apache
Working on : Browser Like Firefox, IE
Conclusion
In this paper, we proposed a new VM placement algorithm for IaaScloud called MOVMP. Wehavedevised aresource usage factor (RUF) in the algorithm to maximize the resource usage of PMs during the placement of VMs. We also presented a multi-dimensional resource usage model, which aimed to minimize the number of under-loaded PMs in the IaaS cloud. This model also helps to improve resource utilization in a balanced manner and migrate fewer VMs, resulting in minimizing resource wastage, power consumption, and violations of SLA.
