A Virtual Machine Scheduling Method Supporting Cloud Data Center Energy Consumption Optimization

Abstract

The invention discloses a virtual machine scheduling method supporting energy consumption optimization of a cloud data center. Machine list; Step 2: Obtain the free space of the running physical machine in Step 1 according to the occupation status of the virtual machine instance; Step 3: Use heuristic retrieval based on the resource requirements of the virtual machine and the free space of the physical machine obtained in Step 2 , to obtain a feasible virtual machine migration strategy; Step 4: Calculate the energy consumption value of the cloud data center for task execution and virtual machine migration; Step 5: Based on the virtual machine migration strategy obtained in Step 3, use Step 4 to calculate the virtual machine migration operation A collection of energy consumption values ​​generated by the cloud data center; Step 6: According to the energy consumption values ​​obtained in Step 5, select the virtual machine migration strategy with the best energy consumption as the final virtual machine scheduling strategy.

Description

technical field [0001] The invention relates to the fields of computer data processing and cloud computing, and is particularly suitable for resource management and resource scheduling for cloud data centers to optimize energy consumption. Background technique [0002] Since Google proposed the concept of cloud computing technology, cloud computing technology has gradually penetrated into all walks of life for data storage and processing. Currently, a large number of enterprises and organizations completely or partially migrate applications running locally to public cloud platforms to reduce local data center management costs and hardware investment costs. From the perspective of cloud data center resource managers, it is necessary to ensure the sustainable development of the data center while meeting user resource requirements. The resources deployed in the cloud data center continue to grow, especially in the era of big data, data storage, processing and communication nee...

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