Virtual machine placement method based on multi-objective optimization in cloud computing

A multi-objective optimization and virtual machine technology, which is applied in the field of cloud computing, can solve problems such as virtual machine migration application performance, application load overload, and stimulation, so as to ensure service quality and avoid frequent migration.

Inactive Publication Date: 2019-03-08
WUHAN UNIV OF SCI & TECH
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  • Abstract
  • Description
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Problems solved by technology

[0003] At present, constrained programming and genetic algorithms are often used to solve the above problems, but the load stability factors of each physical node in the cloud platform are ignored, resulting in the emergence of new resource hotspots or applications in the physical nodes in the new virtual machine placement method in the near future. Overload and other states stimulate new resource configuration requests, leading to frequent virtual machine migrations and resulting in application performance degradation and other issues

Method used

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  • Virtual machine placement method based on multi-objective optimization in cloud computing
  • Virtual machine placement method based on multi-objective optimization in cloud computing
  • Virtual machine placement method based on multi-objective optimization in cloud computing

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[0050] In order to further understand the present invention, the preferred embodiments of the present invention are described below in conjunction with examples, but it should be understood that these descriptions are only for further illustrating the features and advantages of the present invention, rather than limiting the claims of the present invention.

[0051] The basic idea of ​​the present invention is: the current mapping state of the virtual machine and the physical node is represented by group coding, and it is regarded as an individual of the initial generation population. Randomly generate other PSIZE-1 individuals of the initial generation population. Based on the initial generation population, with the individual stability time and migration times as the optimization goals, the genetic algorithm is executed to generate the GSIZE generation population. In the GSIZE generation population, select T gain The individual with the largest value is the group code of th...

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Abstract

The invention discloses a virtual machine placement method based on multi-objective optimization during cloud computing. Based on current information and forecast future information of resources demands of all virtual machines, new mapping is set up among the multiple virtual machines and multiple physical nodes. Therefore, service quality of all applications is ensured and stability of all the physical nodes is greatly enhanced in a novel virtual machine placement scheme. In the meantime, migration of a large number of virtual machines is avoided during the process of shifting from an old placement state to a new placement state for virtual machines. By adoption of the scheme, quality of service is ensured when the multiple virtual machines are replaced. The migration frequency of the virtual machines is low. The long stabilization time of all the physical nodes is ensured in the meantime.

Description

technical field [0001] The invention relates to the field of cloud computing, in particular to a method for placing a virtual machine based on multi-objective optimization in a cloud environment. Background technique [0002] Cloud computing services provide users with computing resources such as data processing and storage, and users can deploy or run applications in the virtual resources they apply for without knowing the details of the computing resource provision process. The system virtualization technology makes it possible to dynamically configure resources, realize resource allocation on demand, and improve resource utilization. With the increasing scale of the data center, the number of cloud platform servers continues to increase, and the resource requirements of user applications are also constantly changing. It is urgent to improve the dynamic resource scheduling capabilities of the cloud platform. Under the premise of ensuring the service quality of user applica...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F9/455G06N3/12
CPCG06F9/45558G06F2009/4557G06N3/12
Inventor 邓莉姚力
Owner WUHAN UNIV OF SCI & TECH
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