Optimizing Data Flow in Multi-Cloud Environments: A Technical Deep Dive
DOI:
https://doi.org/10.32628/CSEIT251112154Keywords:
Multi-Cloud Architecture, Data Flow Optimization, Edge Computing Integration, Cloud Performance Management, Distributed Systems SecurityAbstract
The widespread adoption of multi-cloud strategies has fundamentally transformed enterprise computing architectures, introducing opportunities and challenges in modern IT environments. This article examines data flow optimization between multiple cloud providers, focusing on performance constraints, integration complexities, and security requirements. The article investigates advanced optimization techniques, including direct cloud interconnection, data fabric implementation, intelligent replication strategies, and edge computing integration. Through this article, enterprise deployments across various sectors, the article demonstrates that properly implemented multi-cloud optimization strategies significantly enhance operational resilience, reduce costs, and improve system performance. The article highlights the importance of standardized APIs, comprehensive monitoring frameworks, and emerging AI-driven optimization approaches in achieving efficient multi-cloud operations. This article provides valuable insights for organizations seeking to optimize their multi-cloud environments while maintaining security and compliance requirements.
Downloads
References
Rajesh Kotha, “Multi-Cloud Strategies for Enhanced Resilience and Flexibility,” December 2023. Available: https://www.researchgate.net/publication/383617187_Multi-Cloud_Strategies_for_Enhanced_Resilience_and_Flexibility
Larysa Globa and Anton Kartashov, “OPTIMIZING DISTRIBUTED DATA STORAGE IN MULTI-CLOUD ENVIRONMENTS: ALGORITHMIC APPROACH,” December 2024. Available: https://www.researchgate.net/publication/387398134_OPTIMIZING_DISTRIBUTED_DATA_STORAGE_IN_MULTI-CLOUD_ENVIRONMENTS_ALGORITHMIC_APPROACH
Alexandru Iosup, et al, “Performance Analysis of ComCloud Computing Services for Many-Tasks Scientific puting,” IEEE Transactions on Parallel and Distributed Systems, July 2011. Available: https://www.researchgate.net/publication/224221699_Performance_Analysis_of_Cloud_Computing_Services_for_Many-Tasks_Scientific_Computing
Anthony Lawrence Paul, “Security Challenges and Solutions in Multi-Cloud Environment,” June 2024. Available: https://www.researchgate.net/publication/381074289_Security_Challenges_and_Solutions_in_Multi-Cloud_Environments
Hayfaa Subhi, et al, “Performance Analysis of Enterprise Cloud Computing: A Review,” ResearchGate, February 2023. Available: https://www.researchgate.net/publication/368297975_Performance_Analysis_of_Enterprise_Cloud_Computing_A_Review
Kuanishbay Sadatdiynov, et al, “A review of optimization methods for computation offloading in edge computing networks,” Digital Communications and Networks, Volume 9, Issue 2, April 2023, Pages 450-461. Available: https://www.sciencedirect.com/science/article/pii/S2352864822000244
Karwan Jameel Merseedi, Subhi R M Zeebaree, “Cloud Architectures for Distributed Multi-Cloud Computing: A Review of Hybrid and Federated Cloud Environment,” April 2024. Available: https://www.researchgate.net/publication/380576736_Cloud_Architectures_for_Distributed_Multi-Cloud_Computing_A_Review_of_Hybrid_and_Federated_Cloud_Environment
Harshavardhan Nerella, Prasanna Sai Puvvada,Sivanagaraju Gadiparthi, “AI-Driven Cloud Optimization: A Comprehensive Literature Review,” May 2024. Available: https://www.researchgate.net/publication/381499158_AI-Driven_Cloud_Optimization_A_Comprehensive_Literature_Review
Downloads
Published
Issue
Section
License
Copyright (c) 2025 International Journal of Scientific Research in Computer Science, Engineering and Information Technology
This work is licensed under a Creative Commons Attribution 4.0 International License.