A Systematic Parameter Analysis of Cloud Simulation Tools in Cloud Computing Environments

被引:8
|
作者
Shahid, Muhammad Asim [1 ]
Alam, Muhammad Mansoor [1 ,2 ,3 ,4 ]
Su'ud, Mazliham Mohd [3 ]
机构
[1] Univ Kuala Lumpur, Malaysian Inst Informat Technol, Kuala Lumpur 50250, Malaysia
[2] Riphah Int Univ, Fac Comp, Sect 1-14,Hajj Complex, Islamabad 46000, Pakistan
[3] Multimedia Univ, Persiaran Multimedia, Cyberjaya 63100, Malaysia
[4] Univ Technol Sydney, Sch Comp Sci, 15 Broadway, Ultimo, NSW 2007, Australia
来源
APPLIED SCIENCES-BASEL | 2023年 / 13卷 / 15期
关键词
architecture of cloud simulators; cloud computing; categories of cloud simulators; parameters; processing elements; simulation tools;
D O I
10.3390/app13158785
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
To provide various applications in various domains, a large-scale cloud data center is required. Cloud computing enables access to nearly infinite computing resources on demand. As cloud computing grows in popularity, researchers in this field must conduct real-world experiments. Configuring and running these tests in an actual cloud environment is costly. Modeling and simulation methods, on the other hand, are acceptable solutions for emulating environments in cloud computing. This research paper reviewed several simulation tools specifically for cloud computing in the literature and presented the most effective simulation methods in this research domain, as well as an analysis of a variety of cloud simulation tools. Cloud computing tools such as CloudSim, CloudSim Plus, CloudAnalyst, iFogSim, and CloudReports were evaluated. Furthermore, a parametric evaluation of cloud simulation tools is presented based on the identified parameters. Several 5-parameter tests were performed to demonstrate the capabilities of the cloud simulator. These results show the value of our proposed simulation system. CloudSim, CloudSim Plus, CloudAnalyst, iFogSim, and CloudReports are used to evaluate host processing elements, virtual machine processing elements, cloudlet processing elements, userbase average, minimum, and maximum, and cloudlet ID Start Time, Finish Time, Average Start, and Average Finish for each simulator. The outcomes compare these five simulator metrics. After reading this paper, the reader will be able to compare popular simulators in terms of supported models, architecture, and high-level features. We performed a comparative analysis of several cloud simulators based on various parameters. The goal is to provide insights for each analysis given their features, functionalities, and guidelines on the way to researchers' preferred tools.
引用
收藏
页数:37
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