Virtual machine load balancing method under cloud environment

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

Active Publication Date: 2018-06-19
FUZHOU UNIV
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  • Abstract
  • 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 v

Method used

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  • Virtual machine load balancing method under cloud environment
  • Virtual machine load balancing method under cloud environment
  • Virtual machine load balancing method under 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 of the task request, the requested memory size, the task data scale and task execution Time: According to the above attributes, a random forest regression model based on the CART decision tree is constructed with the CPU usage requested by the task, the requested memory size, and the task data size as the input, and the tas...

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Abstract

The invention relates to the technical field of cloud computing, in particular to a virtual machine load balancing method under a cloud environment. The method comprises the following steps that a random forest regression model is built according to a historical task data set of a cloud platform; a current task set and a current virtual machine set of the cloud platform are obtained; by using thebuilt random forest regression model, execution time of each task in the current task set of the cloud platform is forecast; according to the CPU application amount, memory application amount and taskdata processing scale which are requested to the cloud platform by each task in the current task set of the cloud platform and forecast task execution time, a particle swarm optimization algorithm isused, the load balance degree of a virtual machine in the cloud platform serves as an optimization objective, and a globally optimal particle code is obtained; the globally optimal particle code is decoded into a task-to-virtual machine allocation scheme and output. Accordingly, the total task execution time can be shortened while the resource utilization rate of the virtual machine is balanced.

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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IPC IPC(8): G06F9/50
CPCG06F9/505
Inventor 陈羽中郭文忠江伟
Owner FUZHOU UNIV
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