Abstract:

On the private cloud platform, it cannot be flexible to monitor and distribute the virtual machine memory resources effectively using the existing methods. To solve this problem, a Memory Monitor and Scheduler (MMS) model was put forward. And the real-time monitoring and dynamic scheduling of the virtual machine memory shortage and memory free were realized by using the libvirt function library and libxc function library provided by Xen. A small private cloud platform was built using Eucalyptus with regarding one physical machine as master node and two physical machines as child nodes. In the experiments, when the state of host was in memory shortage, MMS system effectively released the memory space by starting the virtual machine migration strategy; when the memory of the virtual machine was approaching the initial maximum memory, MMS system assigned it with a new maximum memory; when the occupied memory decreased, MMS system recycled part of free memory resource, which has little effect on the performance of virtual machines if the release memory did not exceed 150MB (maximum memory is 512MB). The results show that the MMS model of private cloud platform is effective for real-time monitoring and dynamic scheduling of the memory.