An Algorithm for Cloud-based Web Service Combination Optimization Through Plant Growth Simulation

doi:10.16182/j.issn1004731x.joss.23-0830E

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 light-induced 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.

Key words: cloud-based service, scheduling algorithm, resource constraint, load optimization, cloud computing, plant growth simulation algorithm

CLC Number:

TP391

Li Qiang, Qin Huawei, Qiao Bingqin, Wu Ruifang. An Algorithm for Cloud-based Web Service Combination Optimization Through Plant Growth Simulation[J]. Journal of System Simulation, 2025, 37(2): 462-473.

Figures/Tables 11

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Indicators	Category
Processor utilization	Service
Memory utilization	Service
Disk utilization	Service
I/O utilization	Service
Network utilization	Service

Plant type	L	μ	ν
Stipa grandis	1.215	2.618	0.043
Artemisia frigida willd	3.178	2.760	0.067
Leymus chinensis	0.213	2.132	0.071
Agropyron cristatum	0.166	1.758	0.039

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