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Optimizing Multi-Cloud Data Integration for High-Quality Assurance A Quantum Computing Approach to Scalability and Fault Tolerance

Author(s) Raghavender Maddali
Country India
Abstract The growth of cloud computing, efficient multi-cloud data integration remains an urgent concern. This article explores a quantum computing solution to optimize data harmonization in distributed cloud environments with high-quality guarantee, scalability, and fault tolerance. Quantum algorithms enhance anomaly detection and data synchronization, enhancing efficiency in complex cloud infrastructures. With quantum parallelism, the proposed scheme accelerates data processing, reduces latency, and saves resources. The article covers actual-world deployments and points out the advantages of quantum-boosted security, forecast analytics, and dynamic load balancing. Comparison with traditional methods proves to have tremendous performance improvement in reliability as well as computational speed. Besides, problems related to noise in quantum systems, algorithmic complexity, and hardware limitations are discussed. The results propel cloud security, big data processing, and high-performance computing by merging quantum technology with cloud infrastructure.
Keywords Multi-cloud integration, quantum computing, data harmonization, anomaly detection, fault tolerance, scalability, cloud security, high-performance computing.
Field Computer > Data / Information
Published In Volume 2, Issue 2, February 2021
Published On 2021-02-02
Cite This Optimizing Multi-Cloud Data Integration for High-Quality Assurance A Quantum Computing Approach to Scalability and Fault Tolerance - Raghavender Maddali - IJLRP Volume 2, Issue 2, February 2021. DOI 10.5281/zenodo.15107531
DOI https://doi.org/10.5281/zenodo.15107531
Short DOI https://doi.org/g8986c
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