A MICROSERVICE SOLUTION FOR PREDICTING ELECTRICITY POWER CONSUMPTION IN A CLOUD ENVIRONMENT
DOI:
https://doi.org/10.24867/23BE02NosovicKeywords:
Cloud computing, Microservice arhitecture, Platform as a service, Machine learningAbstract
Description, analysis and presentation of machine learning model training execution time results and prediction of electricity power consumption. Presentation of execution time results tested on various Cloud computing platforms based on the PaaS model of Cloud computing.
References
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[5] EdPrice-MSFT, “Microservice architecture style - azure architecture center,” Azure Architecture Center | Microsoft Learn. [Online]. Available: https://learn.microsoft.com/en-us/azure/architecture/guide/architecture-styles/microservices. [Accessed: 24-Oct-2022].
[2] S. Bradshaw, C. Millard, and I. Walden, “Contracts for clouds: Comparison and analysis of the terms and conditions of cloud computing services”, International Journal of Law and Information Technology, vol. 19, no. 3, pp. 187–223, 2011.
[3] S. Bhardwaj, L. Jain, and S. Jain, “Cloud computing: A study of infrastructure as a service (IAAS)” International Journal of engineering and information Technology, vol. 2, no. 1, pp. 60-63, 2010.
[4] K. Gurudatt, P. Khatawkar, and J. Gambhir. “Cloud computing-platform as service”, International Journal of Engineering, vol. 1, 2011.
[5] EdPrice-MSFT, “Microservice architecture style - azure architecture center,” Azure Architecture Center | Microsoft Learn. [Online]. Available: https://learn.microsoft.com/en-us/azure/architecture/guide/architecture-styles/microservices. [Accessed: 24-Oct-2022].
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Published
2023-07-06
Issue
Section
Electrotechnical and Computer Engineering
