Virtual machine scheduling method for supporting energy consumption optimization of cloud data center

Abstract

The invention discloses a virtual machine scheduling method for supporting energy consumption optimization of a cloud data center. The method comprises the following steps that firstly, a data set isrecorded based on the occupancy of a virtual machine case, and a list of physical machines in a running state in the cloud data center and a list of virtual machines in a running state in the cloud data center are obtained; secondly, according to the occupancy state of the virtual machine case, the free space of the physical machines in the running state in the first step is obtained; thirdly, according to the resource requirements of the vertical machines and the free space, obtained in the second step, of the physical machines, heuristic search is adopted, and feasible virtual machine migration strategies are obtained; fourthly, energy consumption values of the cloud data center for task execution and virtual machine migration are calculated; fifthly, according to the virtual machine migration strategies obtained in the third step, a set of the energy consumption values generated by the cloud data center after virtual machine migration operation is calculated by using the fourth step; sixthly, according to the energy consumption values obtained in the fifth step, the virtual machine migration strategy which is optimal in energy consumption is selected as the final virtual machinescheduling 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...

AI Technical Summary

Problems solved by technology

With the widespread application of virtual machine migration technology, the energy consumption of communication equipment in cloud data centers is increasing, which will bring technical challenges to the construction of green cloud data centers

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