Modeling of Resource Granularity and Utilization with Virtual Machine Splitting

The increasing trend in IT users and their needs for computational power in cloud data centers leads to noticeable growth in physical servers. It is a challenging issue which causes the dramatic burden of power consumption and the number of Physical machines. Virtualization is remarkable method for reducing the number of physical servers with appropriate processing performance and utilization. But, it is worth saying that the fulfilling the resource utilization is still one of the significant challenging issue, especially in in data centers environment. Actually, there are some applications situated on a large single virtual machine. One way to guarantee the reasonable physical server utilization is to let the application to be split and hosted on smaller virtual machines with the sufficient computational power. Although exploiting multiple small virtual machine instead of one large virtual machine benefits appropriate physical resources utilization and reducing the number of turn on physical machine, it is sustained penalty in terms of demanding extra resources due to map the applications on new virtual machines. However, existing research have not clarified precisely the reason in terms of that the data center is sustained extra resources and computational power overhead due to splitting the original application and exploiting more smaller virtual machines provided to preserve the criteria of the original application on the large virtual machine. This paper demonstrates through mathematical modelling that the physical resource providers, which are situated in cloud data center, endure the penalty in terms of extra physical resources. The mentioned mathematical modeling in this paper will be noticeable in cloud data center energy efficiency and physical resource utilization performance.