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Cloud data center energy saving method based on DVS and improved ant colony algorithm

A cloud data center, ant colony algorithm technology, applied in energy-saving computing, data processing power supply, electrical digital data processing, etc., can solve the single energy-saving scheme, the cloud data center energy-saving task scheduling method is not perfect, and does not consider energy consumption issues, etc. problems, to achieve the effect of reducing energy consumption, shortening task scheduling and execution time

Pending Publication Date: 2017-07-14
CHINA UNIV OF PETROLEUM (EAST CHINA)
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AI Technical Summary

Problems solved by technology

However, these algorithms only consider the optimization of performance, and do not consider the issue of energy consumption
[0005] To sum up, the existing energy-saving task scheduling methods for cloud data centers are not perfect, and the energy-saving scheme is too single

Method used

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  • Cloud data center energy saving method based on DVS and improved ant colony algorithm
  • Cloud data center energy saving method based on DVS and improved ant colony algorithm
  • Cloud data center energy saving method based on DVS and improved ant colony algorithm

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Embodiment Construction

[0051] The technical scheme of the present invention is described in detail below in conjunction with accompanying drawing:

[0052] Cloud data center control flow, its basic model is as follows: figure 1 As shown, after the task arrives, it enters the waiting queue. The DVS integrated manager includes two parts: the DVS controller and the data center monitoring platform. The DVS controller dynamically adjusts the voltage according to the host load, and the data center monitoring platform is responsible for monitoring the status of each host and virtual machine. And transmit its data to the load balancing manager, combined with the calculation of the amount of waiting tasks to determine the available virtual machine resources, the task scheduler obtains the available virtual machine resources and the task information in the waiting queue, and uses the improved ant colony algorithm to obtain the optimal solution for performance-energy consumption , and finally assign tasks.

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Abstract

The invention provides a cloud data center energy saving method based on a DVS and an improved ant colony algorithm and relates to the field of cloud computing. According to the method, a DVS technology is combined with an optimized ant colony algorithm task scheduling technology, comprehensive electricity saving management is performed on a cloud data center from the two aspects of physical control and task scheduling algorithm, and a low energy consumption goal is achieved while load balance and optimal performance are guaranteed. By use of a DVS integrated manager, server voltage can be adjusted dynamically according to the load condition; by use of a load balance manager, an alternative virtual machine can be selected before task scheduling for selection of a task to be scheduled, and therefore the purpose of load balance can be achieved; the improved ant colony scheduling algorithm is adopted in a task scheduler, performance factors and energy consumption factors are fused into the scheduling algorithm, therefore, task scheduling and executing time is shortened, and energy consumption is lowered.

Description

technical field [0001] The invention relates to the technical field of energy-saving algorithms for cloud data centers, in particular to an energy-saving method for cloud data centers based on DVS and improved ant colony algorithm. Background technique [0002] Cloud computing is a new computing model developed from grid computing, and it is the product of the fusion of various technologies. Cloud computing service providers are committed to providing users with efficient and convenient computing services, such as IaaS, PaaS, and SaaS. The cloud computing model greatly facilitates users, so that they do not need to purchase and configure complex computing equipment, but only need to apply for computing resources according to their own needs and pay the corresponding fees, and at the same time reduce expenses. Cloud computing service providers will dynamically expand or reduce the scale of cloud computing systems according to usage conditions. [0003] With the advent of th...

Claims

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Application Information

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IPC IPC(8): G06F1/32G06F9/455
CPCG06F1/329G06F9/45558G06F2009/4557Y02D10/00
Inventor 庞善臣张伟光徐建朋马同茂郝少华
Owner CHINA UNIV OF PETROLEUM (EAST CHINA)
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