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Cloud computing resource scheduling realization method based on improved genetic algorithm

A genetic algorithm and resource scheduling technology, applied in genetic rules, computing, resource allocation, etc.

Inactive Publication Date: 2016-07-06
BEIJING UNIV OF TECH
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Since the cloud computing task scheduling strategy needs to take into account the benefits of the cloud service provider while satisfying the user's QoS constraints, there is no mature approach to these problems.

Method used

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  • Cloud computing resource scheduling realization method based on improved genetic algorithm
  • Cloud computing resource scheduling realization method based on improved genetic algorithm
  • Cloud computing resource scheduling realization method based on improved genetic algorithm

Examples

Experimental program
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Embodiment Construction

[0033] In order to verify the performance of the improved genetic algorithm proposed by the present invention in the scheduling of cloud computing resources, the model is tested on the Cloudsim cloud computing simulator. All experiments are run in Eclipse environment such as figure 2 Shown is a display of the experimental results.

[0034] (1) When the number of iterations is different, the fitness value of the optimal individual in the population. The abscissa is the number of algorithm iterations, and the ordinate is the fitness value of the optimal individual in the population. It can be seen that with the increase of the number of population iterations, the fitness value of the optimal individual continues to rise, indicating that the improved algorithm has strong global search ability and good convergence.

[0035] (2) In order to prove the advantages of the improved algorithm proposed by the present invention, this algorithm was compared with the existing random alloc...

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Abstract

The invention relates to a cloud computing resource scheduling realization method based on an improved genetic algorithm. With the development of cloud computing, the scale of a data center is large, the energy consumption problem and the resource utilization rate become main restraining factors, so that on the basis of meeting the user requirements, how to design a reasonable resource scheduling method, to improve the resource utilization rate and to reduce the energy consumption become urgent problems to be solved, and the problems are one of the bottlenecks of the cloud computing development at present. According to the method, the genetic algorithm is improved and is applied to the cloud computing resource scheduling. SLA constraint and energy consumption constraint are used as fitness functions, so that a virtual machine can find a most proper placement strategy when being created on a physical machine; and on the basis of meeting the user requirements, the improved genetic algorithm can reduce the energy consumption and can generate the optimal economic benefit to the greatest degree.

Description

technical field [0001] The invention relates to resource scheduling of cloud computing, uses an improved genetic algorithm to realize the scheduling problem of cloud computing, and belongs to the fields of artificial intelligence and cloud computing. Background technique [0002] Due to various advantages such as high reliability, versatility, high scalability, on-demand service, and low cost, cloud computing has developed rapidly at home and abroad in recent years. Cloud computing is provided to users as a commercial service, and the reasonable scheduling and use of system resources has become a key issue. The resource scheduling of cloud computing is different from traditional resource scheduling. Due to the characteristics of heterogeneity, dynamics, and large-scale nature of cloud computing, tasks in the cloud environment may be generated concurrently at any time, and in most cases, the distribution is uneven. How to reasonably schedule the resources on heterogeneous no...

Claims

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Application Information

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IPC IPC(8): G06F9/455G06F9/50G06N3/12
CPCG06F9/45558G06F9/5061G06F2009/4557G06N3/126Y02D10/00
Inventor 竹翠仇瑞琪
Owner BEIJING UNIV OF TECH
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