With the rapid development of Internet technology, cloud computing has gradually been widely used in people's lives. However, due to the huge and complex data volume, limited storage space and maintenance difficulties, there are still some problems in cloud monitoring data analysis. This paper intends to use the combination of machine learning to study the analysis and experimental simulation of cloud monitoring data, in order to improve the data processing ability of the monitoring system. This paper mainly uses the experimental analysis method and information entropy to study the cloud monitoring system and its data processing and analysis capabilities. The experimental data show that the error of computer tools is less than 6%, which shows that the method is feasible and worthy of application.

Rui Li. Cloud Monitoring Data Analysis and Simulation Based on Machine Learning. Machine Learning Theory and Practice (2022), Vol. 3, Issue 3: 52-59. https://doi.org/10.38007/ML.2022.030307.

[1] Ranya M. M. Salem, M. Sabry Saraya, Amr M. T. Ali-Eldin: An Industrial Cloud-Based IoT System for Real-Time Monitoring and Controlling of Wastewater. IEEE Access 10: 6528-6540 (2022). https://doi.org/10.1109/ACCESS.2022.3141977

[2] Madanjit Singh, Sarveshwar Bharti, Harjit Kaur, Vaibhav Arora, Munish Saini, Manevpreet Kaur, Jaswinder Singh: A Facial and Vocal Expression Based Comprehensive Framework for Real-Time Student Stress Monitoring in an IoT-Fog-Cloud Environment. IEEE Access 10: 63177-63188 (2022). https://doi.org/10.1109/ACCESS.2022.3183077

[3] Kashif Mehboob Khan, Junaid Arshad, Waheed Iqbal, Sidrah Abdullah, Hassan Zaib: Blockchain-Enabled Real-Time SLA Monitoring for Cloud-Hosted Services. Clust. Comput. 25(1): 537-559 (2022). https://doi.org/10.1007/s10586-021-03416-y

[4] Munish Bhatia, Sapna Kumari: A Novel IoT-Fog-Cloud-based Healthcare System for Monitoring and Preventing Encephalitis. Cogn. Comput. 14(5): 1609-1626 (2022). https://doi.org/10.1007/s12559-021-09856-3

[5] Berken Utku Demirel, Islam Abdelsalam Bayoumy, Mohammad Abdullah Al Faruque: Energy-Efficient Real-Time Heart Monitoring on Edge-Fog-Cloud Internet of Medical Things. IEEE Internet Things J. 9(14): 12472-12481 (2022). https://doi.org/10.1109/JIOT.2021.3138516

[6] Ali Reza Shamshiri, M. B. Ghaznavi-Ghoushchi, Ali Reza Kariman: ML-Based Aging Monitoring and Lifetime Prediction of IoT Devices with Cost-Effective Embedded Tags for Edge and Cloud Operability. IEEE Internet Things J. 9(10): 7433-7445 (2022). https://doi.org/10.1109/JIOT.2021.3116065

[7] Dennis A. Martillano, Marco C. Iligan, Algerica Raeven R. Ramos, Allan Daraman Jr. March Fernan H. Abadines: Wearable Tool for Breathing Pattern Recognition and Exacerbation Monitoring for COPD Patients via a Device-to-Cloud Communication Model. J. Commun. 17(6): 423-433 (2022). https://doi.org/10.12720/jcm.17.6.423-433

[8] Maad M. Khalill, Anatoly D. Khomonenko, M. D. Matushko: Measuring the Effect of Monitoring on a Cloud Computing System by Estimating the Delay Time of Requests. J. King Saud Univ. Comput. Inf. Sci. 34(7): 3968-3972 (2022). https://doi.org/10.1016/j.jksuci.2021.02.001

[9] Jerico Moeyersons, Sarah Kerkhove, Tim Wauters, Filip De Turck, Bruno Volckaert: Towards Cloud-Based Unobtrusive Monitoring in Remote Multi-Vendor Environments. Softw. Pract. Exp. 52(2): 427-442 (2022). https://doi.org/10.1002/spe.3029

[10] David Hästbacka, Jari Halme, Laurentiu Barna, Henrikki Hoikka, Henri Pettinen, Martin Larrañaga, Mikael Björkbom, Heikki Mesiä, Antti Jaatinen, Marko Elo: Dynamic Edge and Cloud Service Integration for Industrial IoT and Production Monitoring Applications of Industrial Cyber-Physical Systems. IEEE Trans. Ind. Informatics 18(1): 498-508 (2022). https://doi.org/10.1109/TII.2021.3071509

[11] Ankit Agarwal: Cloud Internet of Things Based Machine Monitoring Analysis of Energy Parameters Using Novel Techniques. Wirel. Pers. Commun. 124(2): 1789-1814 (2022). https://doi.org/10.1007/s11277-021-09431-x

[12] Jacob John, Mariam Sunil Varkey, Riya Sanjay Podder, Nilavrah Sensarma, Munuswamy Selvi, S. V. N. Santhosh Kumar, Arputharaj Kannan: Smart Prediction and Monitoring of Waste Disposal System Using IoT and Cloud for IoT Based Smart Cities. Wirel. Pers. Commun. 122(1): 243-275 (2022). https://doi.org/10.1007/s11277-021-08897-z

[13] Priscila Cedillo, Emilio Insfrán, Silvia Abrahão. Jean Vanderdonckt: Empirical Evaluation of a Method for Monitoring Cloud Services Based on Models at Runtime. IEEE Access 9: 55898-55919 (2021). https://doi.org/10.1109/ACCESS.2021.3071417

[14] Özgün Yilmaz, Levent Görgü, Michael J. O'Grady, Gregory M. P. O'Hare: Cloud-Assisted Mobile Crowd Sensing for Route and Congestion Monitoring. IEEE Access 9: 157984-157996 (2021). https://doi.org/10.1109/ACCESS.2021.3129932

[15] Chetan M. Bulla, Mahantesh N. Birje: A Multi-Agent-Based Data Collection and Aggregation Model for Fog-Enabled Cloud Monitoring. Int. J. Cloud Appl. Comput. 11(1): 73-92 (2021). https://doi.org/10.4018/IJCAC.2021010104

[16] Rajendra Kumar Dwivedi, Rakesh Kumar, Rajkumar Buyya: Secure Healthcare Monitoring Sensor Cloud with Attribute-Based Elliptical Curve Cryptography. Int. J. Cloud Appl. Comput. 11(3): 1-18 (2021). https://doi.org/10.4018/IJCAC.2021070101

[17] Joe-Air Jiang, Jen-Cheng Wang, Chao-Liang Hsieh, Kai-Sheng Tseng, Zheng-Wei Ye, Lin-Kuei Su, Chih-Hong Sun, Tzai-Hung Wen, Jehn-Yih Juang: An Alternative Body Temperature Measurement Solution: Combination of a Highly Accurate Monitoring System and a Visualized Public Health Cloud Platform. IEEE Internet Things J. 8(7): 5778-5793 (2021). https://doi.org/10.1109/JIOT.2020.3034024

[18] Tuan Anh Nguyen, Dugki Min, Eunmi Choi, Jae-Woo Lee: Dependability and Security Quantification of an Internet of Medical Things Infrastructure Based on Cloud-Fog-Edge Continuum for Healthcare Monitoring Using Hierarchical Models. IEEE Internet Things J. 8(21): 15704-15748 (2021). https://doi.org/10.1109/JIOT.2021.3081420