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A resource allocation method for green cloud computing

A technology of resource allocation and cloud computing, applied in the direction of resource allocation, energy-saving computing, multi-programming devices, etc., can solve the problems of limited energy consumption, high virtualization, difficult to determine the processor voltage, etc.

Active Publication Date: 2017-02-15
NANJING UNIV OF POSTS & TELECOMM
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  • Abstract
  • Description
  • Claims
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AI Technical Summary

Problems solved by technology

However, when DVS is applied to the cloud computing system, it will encounter the following problems: (a) the time when the task arrives in the system is uncertain, so the type of the arriving task is difficult to predict; (b) even if the type of task can be predicted, it is suitable for the task It is also difficult to determine the processor voltage; (c) DVS is mainly used to reduce the energy consumption of the host processor, but it is limited to optimize the energy consumption of the entire host or the entire cloud computing system
However, virtualization itself has to pay a high cost of energy efficiency, and the deeper the level of virtualization, the higher the cost

Method used

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  • A resource allocation method for green cloud computing
  • A resource allocation method for green cloud computing
  • A resource allocation method for green cloud computing

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Embodiment Construction

[0067] The specific implementation manners of the present invention will be further described in detail below in conjunction with the accompanying drawings.

[0068] In the resource allocation method designed for green cloud computing in the present invention, in order to improve the resource utilization rate of the cloud computing system and reduce system energy consumption, it is necessary to configure the resources of each physical host in the system to complete the scheduling of virtual machines. During this process, by monitoring the real-time status of the physical host and virtual machine, only the current status of the physical host and virtual machine processing tasks can be obtained, but the resource allocation process always lags behind the user's task request. Therefore, the present invention builds a prediction model, adopts a conservative control strategy, and periodically predicts and controls the request volume of different types of tasks in the cloud computing ...

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Abstract

The invention relates to a resource allocation method for green cloud computing, which uses virtualization technology to abstract the task scheduling problem into a virtual machine deployment problem; predicts the amount of tasks requested by users, and combines the current system status and resource distribution to adopt a conservative approach. Control strategy, allocate and control system resources in advance, reduce energy consumption of cloud computing system, and avoid waste of resources.

Description

technical field [0001] The invention relates to a resource configuration method for green cloud computing. Background technique [0002] Cloud Computing (Cloud Computing) is a hotspot in the computer field at present. It dispatches computing tasks to a resource pool composed of a large number of computing and storage resource nodes, enabling users to obtain computing power, storage space and information services on demand. Cloud computing itself is energy-saving. For example, through virtualization technology, resources can be effectively integrated to improve resource utilization; through shutdown / sleep technology, idle energy consumption can be reduced to reduce energy consumption. With the rapid development of cloud computing technology, traditional data centers have undergone changes, resulting in a new generation of data centers, called cloud data centers (Cloud Data Center). Cloud data centers contain a large number of servers, and the number of these servers continue...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F9/50G06F9/455
CPCY02D10/00
Inventor 徐小龙曹玲玲章韵杨立军李爱群李玉倩
Owner NANJING UNIV OF POSTS & TELECOMM
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