AI-Driven Data Migration Strategies in Multi-Cloud Architectures: Challenges and Innovations
DOI:
https://doi.org/10.63397/ISCSITR-IJSRAIML_2023_04_01_004Keywords:
Multi-Cloud Architecture, AI-Orchestrated Migration, Data Transfer Optimization, Intelligent Workload Management, Cloud Interoperability, Self-Healing Infrastructure, Migration Challenges, Federated Cloud SystemsAbstract
The evolution of cloud computing has ushered in an era where enterprises adopt multi-cloud strategies to leverage cost efficiencies, redundancy, and agility. However, migrating data across heterogeneous cloud platforms introduces unprecedented complexities around latency, security, compliance, and orchestration. This paper investigates how Artificial Intelligence (AI)-driven strategies—such as predictive modeling, intelligent orchestration, and real-time anomaly detection—can streamline data migration in multi-cloud environments. It synthesizes existing literature, identifies core challenges, proposes a reference architecture, and evaluates the performance benefits of AI-augmented data migration.
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