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A virtual machine load balancing method in cloud environment

A virtual machine and cloud environment technology, applied in the field of cloud computing, can solve the problems of not considering the total working time of tasks on the virtual machine, the increase of the total waiting time of tasks, etc.

Active Publication Date: 2021-08-31
FUZHOU UNIV
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  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] At present, most load balancing optimization algorithms focus on the CPU utilization and memory utilization of virtual machines as the main optimization goals, and do not consider the total working hours of tasks on balanced virtual machines, which may easily lead to unfinished tasks in some virtual machines At the same time, another part of the virtual machine has completed the assigned task and is idle, thus increasing the total waiting time of the task

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  • A virtual machine load balancing method in cloud environment
  • A virtual machine load balancing method in cloud environment
  • A virtual machine load balancing method in cloud environment

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Embodiment Construction

[0056] The present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0057] figure 1 It is an implementation flowchart of a virtual machine load balancing method in a cloud environment of the present invention. Such as figure 1 Shown, the inventive method comprises the steps:

[0058] Step A: Build a random forest regression model based on the historical task data set of the cloud platform.

[0059] In the historical task data set, each task task is described by four attribute values, expressed as task={reqCpu, reqMem, reqData, runtime}, which respectively represent the CPU usage requested by the task, the requested memory size, the task data scale, and the task execution Time: According to the above attributes, the CPU usage requested by the task, the requested memory size, and the task data size are used as input, and the task execution time is output, to build a random forest regression model bas...

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Abstract

The present invention relates to the technical field of cloud computing, in particular to a virtual machine load balancing method in a cloud environment, comprising the following steps: constructing a random forest regression model according to the historical task data set of the cloud platform; machine set; use the constructed random forest regression model to predict the execution time of each task in the current task set of the cloud platform; according to the CPU usage, memory usage, and Task data processing scale and predicted task execution time, using particle swarm optimization algorithm, taking the load balance degree of virtual machines in the cloud platform as the optimization goal, to obtain the globally optimal particle code; decode the global optimal particle code into task to The allocation scheme of the virtual machine and output. The method can reduce the total execution time of the task while balancing the resource utilization rate of the virtual machine.

Description

technical field [0001] The invention relates to the technical field of cloud computing (IaaS), in particular to a virtual machine load balancing method in a cloud environment. Background technique [0002] As a new type of business service model, cloud computing is gradually becoming an important development direction of the computer industry, and has attracted more and more attention from researchers and the public. Cloud computing is used to access applications, services and infrastructure anytime, anywhere in an on-demand manner. At the same time, cloud brokers have also raised many difficulties in the field of commercial applications, and the problem of load balancing is one of them. Load balancing refers to sharing work among multiple computing resources, providing users with higher services, utilizing resources efficiently, and enabling applications to achieve good performance. Therefore, in a cloud environment, implementing load balancing is an important aspect to i...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F9/50
CPCG06F9/505
Inventor 陈羽中郭文忠江伟
Owner FUZHOU UNIV