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Cloud computing resource scheduling method based on self-adjusting ion motion algorithm

A technology of ion movement and resource scheduling, applied in computing, resource allocation, energy-saving computing, etc., can solve problems such as single goal, deterioration of other indicators, and no consideration of task overtime cost, etc., to achieve good optimization accuracy, good algorithm stability, The effect of improving resource utilization and management efficiency

Pending Publication Date: 2022-05-20
韦量
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Problems solved by technology

However, most studies do not consider the cost of task overtime, that is, the delay compensation promised by the cloud service provider.
Moreover, most studies are based on a single objective, and the scheduling process tends to over-optimize a certain indicator while deteriorating other indicators

Method used

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  • Cloud computing resource scheduling method based on self-adjusting ion motion algorithm
  • Cloud computing resource scheduling method based on self-adjusting ion motion algorithm
  • Cloud computing resource scheduling method based on self-adjusting ion motion algorithm

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Experimental program
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Embodiment

[0105] In order to further verify the effectiveness of the proposed algorithm, the present invention compares the performance of SAIMO with PSO, IMO [9], IIMO [22], and literature [23] algorithms, and uses 29 typical benchmark function optimization problems (see Table 1 ), as the performance test analysis of this algorithm.

[0106] 1. Parameter setting: SAIMO, IMO[9], PSO, IIMO[22], literature[23] algorithms, the group size of the five algorithms are all set to 40, and the maximum number of iterations is set to 500. The rest of the parameter settings are as follows: For the IMO, IIMO and literature [23] algorithms, keep the same parameter settings as the original paper [9], [22] and [23] respectively.

[0107] Table 1 Test function

[0108]

[0109]

[0110] In order to avoid the impact of randomness on the experimental results, the present invention allows five algorithms to conduct 30 independent experiments on each optimization problem in the experiment, and records...

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Abstract

The invention discloses a self-adjusting ion motion algorithm. The core idea of the algorithm is as follows: an ion individual automatically adjusts a motion mode based on population fitness standard deviation information and the current state of the ion individual. And the algorithm is applied to the field of cloud computing resource scheduling, so that a cloud service provider accelerates a cloud task deployment process, the resource utilization rate and the management efficiency are improved, the operation and maintenance cost is reduced, and the market competitiveness is improved while user requirements are met.

Description

technical field [0001] The invention relates to the application field of swarm intelligence algorithm technology in cloud computing, and relates to a cloud computing resource scheduling method based on a self-adjusting ion motion algorithm. Background technique [0002] Swarm intelligence optimization algorithm can provide reliable solutions when solving complex optimization problems, so since Holland proposed genetic algorithm (GA), research on swarm intelligence optimization algorithm has attracted more and more attention. Ions motion algorithm (IMO) is a new swarm intelligence optimization algorithm proposed by Javidy et al. However, the IMO algorithm still has the problems that it is easy to fall into local optimum prematurely and the convergence speed is slow in the later stage of evolution. Therefore, in order to improve the problem that IMO is prone to fall into local optimum when faced with complex optimization problems, the present invention proposes a self-adjusti...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F9/48G06F9/50
CPCG06F9/4843G06F9/5027Y02D10/00
Inventor 韦量王勇
Owner 韦量
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