Resource state-based virtual machine structure adjustment method and adjustment system
A technology for structure adjustment and resource status, applied in the field of cloud resource virtual machine adjustment, to achieve the effect of improving utilization, optimizing cloud resources, and reducing cost
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Embodiment 1
[0042] A method for adjusting the structure of a virtual machine based on a resource state, comprising the steps of:
[0043] Step 1, collect the cloud resource state data of the virtualization layer and the virtual machine in the cloud resource pool;
[0044] Step 2. Based on the collected cloud resource status data, establish a resource model that represents the current cloud resource pool and physical resources corresponding to the workload. Step 2 further includes current cloud resource cost estimation, multi-tier Web application transition probability estimation, and node service rate Estimation, model parameter estimation and adjustment sub-steps;
[0045] Step 3. Based on the resource model, calculate the phase cost of the multi-layer Web application system, and obtain the virtual machine structure that needs to be allocated for the current phase of the multi-layer Web application system;
[0046] Step 4. According to the calculation result of step 3, send a control in...
Embodiment 2
[0077] A virtual machine structure adjustment system based on resource state, which includes:
[0078] The acquisition and control engine is set on the virtualization layer and virtual machine of the cloud resource pool, and is used to collect the cloud resource status data of the virtualization layer and virtual machine in the cloud resource pool, and adjust the current stage to serve multiple layers according to the control instructions. The virtual machine structure of the Web application system;
[0079] The cloud resource monitoring and control module is used to send control instructions to the acquisition and control engine;
[0080] The cloud resource modeling module is used to establish a resource model representing the physical resources corresponding to the current cloud resource pool and workload. The cloud resource modeling module further includes a cloud resource cost estimation submodule, a multi-tier application transition probability estimation submodule, and a...
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