A cloud resource allocation and scheduling method with energy efficiency priority

Abstract

The invention discloses a cloud resource allocation and scheduling method with energy efficiency priority. On the basis of establishing a cloud resource allocation system model, the method designs a virtual machine allocation method with energy efficiency priority and a dynamic virtual machine migration method, which strengthens cloud resource allocation. energy efficiency management. The virtual machine allocation method uses the extended box packing algorithm to reduce the number of working servers; the dynamic virtual machine migration method uses the linear integer programming method to dynamically integrate virtual machines into the minimum number of cloud servers, further reducing the number of working servers and improving the computing center. energy efficiency. The migration method and the allocation method work together to effectively reduce the total energy consumption of the cloud computing center. The simulation research results show that the cloud resource allocation and scheduling method with energy efficiency priority designed in the present invention can effectively improve the energy efficiency of the cloud computing system.

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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