An Iterative Budget Algorithm for Dynamic Virtual Machine Consolidation Under Cloud Computing Environment
Abstract
Virtualization is a crucial cloud computing technology to allow for flexible use on a pay-as-you-go basis of a significant amount of distributed computing services. An Iterative Budget Algorithm for Dynamic Virtual Machine Consolidation under cloud computing environment As service demand continues to increase to a global scale, efficient virtual machine consolidation is becoming increasingly imperative. Existing heuristic algorithms aimed primarily at minimizing either service level violations or the cloud’s energy consumption.
However, the An Iterative Budget Algorithm for Dynamic Virtual Machine Consolidation under cloud computing environment overhead communication between different virtual machines and the time of virtual machine consolidation decisions are rarely considered. Experiments show that the proposed algorithm provides a substantial improvement over other typical heuristics and metaheuristic algorithms in reducing energy consumption, the number of virtual machines migrated, overall communication overhead, as well as the decision time.
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
This paper presented a new iterative budget algorithm for solving the problem of VM consolidation. This paper’s main contributions are as follows. The overall cost of migration, overhead communication and energy consumption are analyzed in detail and modeled with consideration of bandwidth sharing and four resource limit dimensions. This paper presented an iterative VM consolidation budget algorithm on a large scale. We have established a reverse selection mechanism for randomly selected targets to find suitable migrants with the use of a vectordot-based out-migration and in-migration budget.
