一种基于模拟植物生长的Web云服务组合优化算法

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

系统仿真学报 ›› 2025, Vol. 37 ›› Issue (2): 462-473.doi: 10.16182/j.issn1004731x.joss.23-0830E

• 研究论文 • 上一篇

一种基于模拟植物生长的Web云服务组合优化算法

李强¹^,², 秦华伟¹^,², 乔冰琴¹^,², 吴瑞芳¹^,²

^1.山西省财政税务专科学校大数据学院，山西太原 030027
^2.太原理工大学财经学院，山西太原 030027

收稿日期:2023-07-04 修回日期:2023-08-02 出版日期:2025-02-14 发布日期:2025-02-10
通讯作者: 秦华伟

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

Li Qiang¹^,², Qin Huawei¹^,², Qiao Bingqin¹^,², Wu Ruifang¹^,²

^1.School of Big Data, Shanxi Finance & Taxation College, Taiyuan 030027, China
^2.School of Finance and Economics, Taiyuan University of Technology, Taiyuan 030027, China

Received:2023-07-04 Revised:2023-08-02 Online:2025-02-14 Published:2025-02-10
Contact: Qin Huawei
About author:Li Qiang (1980-), male, vice professor, master, research area: intelligent &application.
Supported by:
Shanxi Province Higher Education Science and Technology Innovation Fund Project(2022-676);Shanxi Soft Science Program Research Fund Project(2016041008-6)

摘要/Abstract

摘要：

为提高web云服务的效率，提出一个改进的模拟植物生长算法调度模型。使用数学方法描述web云服务和系统资源之间的约束关系。建立了一个光诱导模型模拟植物生长。通过几种植物类型比较算法的性能，并选择最佳植物模型作为系统的设置。实验结果表明：当测试web云服务的数量达到2 048时，该模型比PSO算法快2.14倍，比蚁群算法快2.8倍，比蜂群算法快2.9倍，比遗传算法快8.38倍。

关键词: 云服务, 调度算法, 资源约束, 负载优化, 云计算, 模拟植物生长算法

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

中图分类号:

TP391

李强,秦华伟,乔冰琴等 . 一种基于模拟植物生长的Web云服务组合优化算法[J]. 系统仿真学报, 2025, 37(2): 462-473.

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.

图/表 11

参考文献 17

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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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一种基于模拟植物生长的Web云服务组合优化算法

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

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