The application relates to the technical field of computer
virtualization and
cloud computing, in particular to a
server virtualization system based on a
virtual machine, which comprises a bottom-layer
virtual machine manager, a state monitoring module, a
jitter quantification module and a decision scheduling module; the state monitoring module collects hardware performance counter data, current physical
resource utilization and
virtual machine resource request data, and analyzes kernel-level running state data; the
jitter quantification module extracts
central processing unit context
switching frequency,
translation lookaside buffer failure times and last-level cache contention indexes, and generates scheduling
jitter entropy values; the decision scheduling module compares the scheduling jitter entropy values with a preset dangerous threshold value, executes a
dynamic resource allocation scheme based on a deep
reinforcement learning model below the threshold value, and executes a static locking degradation scheme when the threshold value reaches or exceeds the threshold value, so that the
instability risk of a virtual
machine monitor can be actively inhibited.