Energy-Aware and Privacy-Enhanced Cloud Scheduling: Integrating AI Frameworks with DC–DC Converter Optimization for Sustainable Oracle Database Operations
DOI:
https://doi.org/10.15680/IJCTECE.2024.0705003Keywords:
Energy-efficient cloud computing, AI framework, DC–DC converter optimization, Oracle databases, privacy-preserving architecture, zero-touch automation, sustainable IT infrastructure, data security, green computing, workload predictionAbstract
The exponential growth of cloud-based Oracle database systems has intensified the demand for energy-efficient and privacy-preserving computing infrastructures. This paper proposes an Energy-Aware and Privacy-Enhanced Cloud Architecture that integrates Artificial Intelligence (AI) frameworks with DC–DC converter optimization for sustainable database operations. The framework emphasizes dynamic power management, secure data handling, and zero-touch automation to improve cloud efficiency and data integrity. AI algorithms are utilized to predict workload variations, optimize voltage regulation, and minimize energy wastage through adaptive DC–DC converter control. Meanwhile, privacy-preserving mechanisms such as differential privacy and homomorphic encryption ensure data confidentiality during AI-driven decision-making. The integration of machine learning-based workload analysis, converter efficiency models, and privacy-centric orchestration layers enhances both sustainability and security. Experimental evaluations demonstrate significant reductions in energy consumption—up to 35%—while maintaining strict compliance with data governance and performance standards. The framework also ensures operational continuity through zero-touch maintenance strategies, enabling automatic resource provisioning and fault recovery. By combining energy-efficient hardware design principles with AI-driven cloud intelligence, this study establishes a foundation for sustainable and privacy-aware Oracle database ecosystems. The proposed architecture provides a scalable and intelligent approach that supports green computing initiatives and fosters resilient, compliant, and energy-optimized cloud operations suitable for enterprise-level database management.
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