Journal of System Simulation
Abstract
Abstract: In order to improve the efficiency of cloud-based web services, an improved plant growth simulation algorithm scheduling model. This model first used mathematical methods to describe the relationships between cloud-based web services and the constraints of system resources. Then, a lightinduced plant growth simulation algorithm was established. The performance of the algorithm was compared through several plant types, and the best plant model was selected as the setting for the system. Experimental results show that when the number of test cloud-based web services reaches 2 048, the model being 2.14 times faster than PSO, 2.8 times faster than the ant colony algorithm, 2.9 times faster than the bee colony algorithm, and a remarkable 8.38 times faster than the genetic algorithm.
Recommended Citation
Li, Qiang; Qin, Huawei; Qiao, Bingqin; and Wu, Ruifang
(2025)
"An Algorithm for Cloud-based Web Service Combination Optimization Through Plant Growth Simulation,"
Journal of System Simulation: Vol. 37:
Iss.
2, Article 13.
DOI: 10.16182/j.issn1004731x.joss.23-0830E
Available at:
https://dc-china-simulation.researchcommons.org/journal/vol37/iss2/13
First Page
462
Last Page
473
CLC
TP391
Recommended Citation
Li Qiang, Qin Huawei, Qiao Bingqin, et al. An Algorithm for Cloud-based Web Service Combination Optimization Through Plant Growth Simulation[J]. Journal of System Simulation, 2025, 37(2): 462-473.
DOI
10.16182/j.issn1004731x.joss.23-0830E
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