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Virtual machine scheduling method based on combination optimization

A scheduling method and combined optimization technology, applied in the field of computer science and technology, can solve the problems of unsatisfactory real-time requirements, poor timeliness of algorithms, and large amount of calculation, so as to avoid operation delay and virtual machine downtime, High real-time, the effect of meeting the requirements of high real-time

Inactive Publication Date: 2015-04-22
XIDIAN UNIV
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AI Technical Summary

Problems solved by technology

Due to the time-consuming operation of virtual machine migration, the timeliness of the algorithm is poor
Zhong.H et al. used genetic algorithm to solve the virtual machine scheduling problem. One of the characteristics of artificial intelligence algorithms such as genetic algorithm is the large amount of calculation, which cannot meet the demand in systems with high real-time requirements.

Method used

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  • Virtual machine scheduling method based on combination optimization
  • Virtual machine scheduling method based on combination optimization
  • Virtual machine scheduling method based on combination optimization

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Embodiment

[0064] Groups are organized in the form of image 3 As shown, the hosts in the cluster are divided into two roles, which are the computing nodes of the control nodes. There is a controller node in the cluster, which is responsible for receiving and responding to virtual resource requests, and dispatching virtual resource requests to physical hosts that provide computing capabilities. The functional modules of the control node mainly include a scheduling module (scheduler) and a data collection module (collector). In addition, the system has several compute nodes, which are physical hosts that can provide computing capabilities and are responsible for creating specific virtual machines to perform computing tasks. There is a virtual machine management module (VM manager) in the computing node. The control node and computing node communicate with each other. The monitoring module on the computing node is responsible for collecting the resource usage of the computing node. When...

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Abstract

The invention discloses a virtual machine scheduling method based on combination optimization. The method can be used for real-time virtual machine scheduling decisions in a virtual cluster, the starting positions of virtual machines can be decided in real time according to the current resource utilization conditions of the virtual cluster so that the number of occupied physical hosts can be minimum; in this way, the resource utilization rate can be increased, and meanwhile energy consumption can be lowered. According to the virtual machine scheduling method, simple mathematical calculation is adopted, a scheduling result can be obtained within limited comparison frequency, and the comparison frequency is related to the type of the virtual machines and the type of the physical hosts. Compared with an artificial intelligence algorithm adopted in the process of traditionally solving a combination optimization problem, the virtual machine scheduling method has high real-time performance and can decide the positions where the virtual machines are placed in real time and meet the requirement for high real-time performance of a virtual machine scheduling system.

Description

technical field [0001] The invention belongs to the field of computer science and technology, and relates to virtual machine scheduling in virtual clusters, in particular to a combined optimization-based virtual machine scheduling method. Background technique [0002] As an emerging high-performance computing method, cloud computing has attracted more and more attention from enterprises. The infrastructure as a service (Infrastructure as a Service) model in cloud computing is a lower layer and widely used service model. In 2006, Amazon released the Elastic Cloud Computing (EC2) service, creating a precedent for IaaS services. After that, various companies launched their own commercial cloud computing platforms, such as Qingyun, Alibaba Cloud, and Tencent Cloud. In addition, IaaS open source platforms such as Nucaluptus and OpenStack have also received extensive attention. IaaS service mainly integrates computing resources to provide users with the infrastructure (CPU, memo...

Claims

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Application Information

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IPC IPC(8): G06F9/455G06F9/50
CPCY02D10/00
Inventor 马建峰刘旭启李金库卢笛
Owner XIDIAN UNIV
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