An Extenics-Based Dynamic Resource Adjustment for the Virtual Machine in Cloud Computing Environment

In order to integrate the system resource, utilize the resources flexibly, and meet the demand of various data management and applications in the cloud computing environment, one of the positive solutions is to apply the virtualization technology. Various applications performed on a virtual platform, the required resources for individual application should be adjusted flexibly and effectively. An extenics-based dynamic resource adjustment mechanism for supporting cloud computing is proposed in this paper. Based on a KVM (Kernel-based Virtual Machine) technology, an associative function has been established by applying the extenics theory to determine the degree of CPU requirement for each application. According to the degree of CPU requirement, the proposed resource adjustment mechanism can provide a proper number of CPUs for each virtual machine dynamically. The experimental results show that the proposed mechanism can improve the performance of the system and distribute the source information effectively in real time.