Quantum Cloud Computing: Opportunities and Challenges
Article Sidebar
Main Article Content
Abstract
Quantum cloud computing combines quantum processing capabilities with cloud-based service delivery to provide advanced computational power to users over the internet. This paper explores the architecture, applications, and challenges of quantum cloud computing systems. The study discusses how quantum algorithms can solve complex optimization, cryptography, and simulation problems more efficiently than classical computing systems. Security concerns, hardware limitations, and high implementation costs are also analyzed. The paper concludes that quantum cloud computing has the potential to revolutionize scientific research, financial modeling, and artificial intelligence applications in the future.
Article Details
References
Foster, I., Zhao, Y., Raicu, I., & Lu, S. (2008). Cloud computing and grid computing 360-degree compared. Grid Computing Environments Workshop, 1–10.
Rao, R. V., Selvamani, K., & Kumar, S. (2011). Security challenges and threats in cloud computing. International Journal of Computer Science and Information Technologies, 2(4), 1706–1711.
Hashem, I. A. T., Yaqoob, I., Anuar, N. B., Mokhtar, S., Gani, A., & Khan, S. U. (2015). The rise of “big data” on cloud computing: Review and open research issues. Information Systems, 47, 98–115.
Amazon Web Services. (2024). Overview of cloud computing. Retrieved from AWS Official Website
Microsoft Azure. (2024). Cloud computing services. Retrieved from Microsoft Azure
Google Cloud. (2024). Google cloud architecture framework. Retrieved from Google Cloud
IBM Cloud. (2024). Hybrid cloud solutions and services. Retrieved from IBM Cloud
Oracle Corporation. (2024). Oracle cloud infrastructure documentation. Retrieved from Oracle Cloud
Bernstein, D. (2014). Containers and cloud: From LXC to Docker to Kubernetes. IEEE Cloud Computing, 1(3), 81–84.
Pahl, C. (2015). Containerization and the PaaS cloud. IEEE Cloud Computing, 2(3), 24–31.
Botta, A., De Donato, W., Persico, V., & Pescapé, A. (2016). Integration of cloud computing and internet of things: A survey. Future Generation Computer Systems, 56, 684–700.
Bellundagi, M. (2023). A Secure API Gateway Framework for Enterprise Applications. International Journal of Science, Technology and Convergence, 5(5).
Bellundagi, M. (2022). Cloud-Native Application Development Using Spring Boot. International Journal of Science, Technology and Convergence, 4(4).
Konda, P. R. (2024). Semantic Emergence Modeling: How AI Systems Develop Higher-Level Understanding from Raw Data. International Meridian Journal, 6(6). https://meridianjournal.in/index.php/IMJ/article/view/118
Konda, P. R. (2018). Integrating LLMs into Financial Data Analysis Workflows for Automated Interpretation and Insights . International Numeric Journal of Machine Learning and Robots, 2(2). https://injmr.com/index.php/fewfewf/article/view/231