Energy efficiency preferential cloud resource allocation and scheduling method

Abstract

The invention discloses an energy efficiency preferential cloud resource allocation and scheduling method. According to the method, on the basis of establishing a cloud resource allocation system model, an energy efficiency preferential virtual machine allocation method and a dynamic virtual machine migration method are designed, and the energy efficiency management of cloud resources is reinforced. According to the virtual machine allocation method, through utilization of an expansion bin packing algorithm, the number of working servers is reduced. According to the dynamic virtual machine migration method, through utilization of an integer linear programming method, virtual machines are dynamically integrated into the least number of cloud servers, the number of the working servers is further reduced, and the energy efficiency of a computing center is improved. The migration method and the allocation method work cooperatively, so the total energy consumption of the cloud computing center can be effectively reduced. A simulation study result shows that according to the energy efficiency preferential cloud resource allocation and scheduling method designed by the invention, the energy efficiency of the cloud computing system can be effectively improved.

Description

technical field [0001] The invention belongs to the field of information technology and relates to the distribution and scheduling of server resources in a cloud computing center, in particular to a cloud resource distribution and scheduling method with energy efficiency priority, which can be used for energy efficiency optimization of servers in a cloud computing environment. Background technique [0002] In modern cloud computing centers, high energy consumption is a key issue that increases operating costs. According to literature statistics, the cost of power and heat dissipation has increased by 4 times in the past 10 years, and more than 50% of cloud computing centers have identified power and heat dissipation costs as the key factors limiting server deployment. Therefore, it is imperative to reduce the energy consumption of cloud computing centers. [0003] In fact, idle servers in cloud centers consume about 70% of peak power, and the waste of electricity consumed b...

AI Technical Summary

Problems solved by technology

The optimal server load virtual machine allocation method mainly considers the balance of server load in the cloud computing center; the virtual machine allocation method that only adopts energy efficiency priority is limited to allocating virtual machines on the server with the best energy efficiency, but the virtual machine will not be hosted on the server after the virtual machine ends. Therefore, the energy saving effect of the above method is not ideal.

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