Cloud Job Scheduling Model Based on Improved Plant Growth Algorithm

Authors

Li Qiang, 1.Department of Information, College of Finance & Economics, Tai yuan University of Technology, Taiyuan 030024, China; ;2.College of Information, Shanxi Finance &Taxation College, Taiyuan 030024, China; ;
Xiaofeng Liu, 3. College of Data Science, Taiyuan University of Technology, Taiyuan 030024, China;

Abstract

Abstract: The performance of cloud job scheduling algorithm has a great importance to the whole cloud system. The key factors that affect cloud operation scheduling are found out, and a resource constraint model is established. The existing simulation plant growth algorithm is improved based on the Logistic model of plant growth law, so that the plant growth way was made to change according to the energy power. The comparison of four different plant models was carried out and their different features were analyzed. Compared with 6 typical cloud job scheduling algorithms, it is concluded that the improved simulation plant growth algorithm based on Logistic model has better job scheduling efficiency.

Recommended Citation

Qiang, Li and Liu, Xiaofeng (2019) "Cloud Job Scheduling Model Based on Improved Plant Growth Algorithm," Journal of System Simulation: Vol. 30: Iss. 12, Article 20.
DOI: 10.16182/j.issn1004731x.joss.201812020
Available at: https://dc-china-simulation.researchcommons.org/journal/vol30/iss12/20

First Page

4649

Revised Date

2018-07-14

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.201812020

Last Page

4658

CLC

TP393;TP181

Recommended Citation

Li Qiang, Liu Xiaofeng. Cloud Job Scheduling Model Based on Improved Plant Growth Algorithm[J]. Journal of System Simulation, 2018, 30(12): 4649-4658.

Corresponding Author

Xiaofeng Liu,

DOI

10.16182/j.issn1004731x.joss.201812020