Application of Machine Learning in Cloud Service Cost Prediction and Resource Optimization
DOI:
https://doi.org/10.71222/tw2j1j90Keywords:
cloud computing, machine learning, cost forecasting, resource optimizationAbstract
With the continuous development of cloud computing, the demand for intelligent cost management and resource optimization is increasing. This paper focuses on the application of machine learning in the whole process of cloud services, including time series modeling, regression analysis and transfer learning in cost prediction, load modeling in resource optimization, reinforcement learning scheduling and multi-tenant allocation mechanism. The research results also verify that machine learning helps cloud service platforms improve prediction accuracy and resource utilization effect and is conducive to building efficient self-adaptive service architecture.
References
1. I. Pintye, J. Kovács, and R. Lovas, "Enhancing machine learning-based autoscaling for cloud resource orchestration," J. Grid Comput., vol. 22, no. 4, pp. 1–31, 2024, doi: 10.1007/s10723-024-09783-1.
2. B. Guindani, D. Ardagna, A. Guglielmi, R. Rocco, and G. Palermo, "Integrating Bayesian optimization and machine learning for the optimal configuration of cloud systems," IEEE Trans. Cloud Comput., vol. 12, no. 1, pp. 277–294, 2024, doi: 10.1109/TCC.2024.3361070.
3. P. Nawrocki and M. Smendowski, "Optimization of the use of cloud computing resources using exploratory data analysis and machine learning," J. Artif. Intell. Soft Comput. Res., vol. 14, no. 4, pp. 287–308, 2024, doi: 10.2478/jaiscr-2024-0016.
4. S. Petale and S. Subramaniam, "CLARA+: dual machine learning optimized resource assignment for translucent SDM-EONs," J. Opt. Commun. Netw., vol. 16, no. 10, pp. F1–F12, 2024, doi: 10.1364/JOCN.527846.
5. P. Nawrocki and M. Smendowski, "FinOps-driven optimization of cloud resource usage for high-performance computing using machine learning," J. Comput. Sci., vol. 79, p. 102292, 2024, doi: 10.1016/j.jocs.2024.102292.
6. O. C. Agomuo, O. W. B. Jnr, and J. H. Muzamal, "Energy-aware AI-based optimal cloud infra allocation for provisioning of resources," in Proc. 2024 IEEE/ACIS 27th Int. Conf. Softw. Eng., Artif. Intell., Netw. Parallel/Distributed Comput. (SNPD), pp. 269–274, Jul. 2024, doi: 10.1109/SNPD61259.2024.10673918.
