Virtual resource dispatching and optimizing method based on cost performance

Abstract

The invention discloses a virtual resource dispatching and optimizing method based on cost performance. When a user applies for resources, the applied resources are configured in their own integration ratio sections; in the system running process, the types of physical servers are periodically judged, and for a heavy load server, a plurality of virtual resources with the small usage rate are migrated to a physical server with the rising integration ratio or the smaller integration ratio in an adjacent section; for a light load server, a plurality of virtual resources with the large usage rate are migrated to a physical server with the descending integration ratio or the larger integration radio in an adjacent section. According to the resource dispatching and optimizing method, on one hand, the high load virtual resources in the same integration ratio section can be migrated to the physical server with the low integration ratio, and the user occupies more physical resources while spending least cost; on the other hand, the light load virtual resources can be migrated to the physical server with the high integration ratio on the premise that the performance is not affected, and operating cost can be reduced.

Description

technical field [0001] The present invention relates to a cost-effective virtualization resource scheduling optimization method, and more specifically, to a cost-effective virtualization method that can effectively balance the user's occupation of physical resources and the virtual machine carried by the cloud platform. Resource scheduling optimization method. Background technique [0002] With the wide application of virtualization technology and the continuous development of cloud computing, data centers have adopted a large number of related physical resource virtualization technologies. Due to the frequent replacement of hardware equipment in the data center, the physical server configuration specifications are uneven, and the corresponding virtualization capabilities are also different. This heterogeneous environment undoubtedly brings great problems to virtual resource scheduling. Moreover, for virtual resource users, in order to maximize the cost-effectiveness of pu...

AI Technical Summary

Problems solved by technology

[0005] From the above overview of the existing scheduling algorithms, it can be seen that the current resource scheduling algorithms are basically resource scheduling based on performance optimization or energy saving purposes, and cannot effectively balance the cost-effectiveness of users and cloud platform resources. The occupied physical resources cannot be reasonably allocated from the perspective of cost performance

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