The rapid expansion of cloud computing infrastructures has significantly increased global energy consumption and carbon emissions, raising concerns about environmental sustainability and operational efficiency in modern data centers (Maheshkar 2026; Singh et al. 2026). This study examines energy-aware and green cloud computing strategies that aim to reduce power usage and environmental impact through intelligent resource management and artificial intelligence-based optimization (Maheshkar 2025; Danach et al. 2026). Using a systematic review and comparative analytical approach, this research evaluates existing frameworks, scheduling techniques, and governance models that support sustainable cloud operations (Noor et al. 2026; Hebbar et al. 2026). The findings indicate that integrating AI-driven orchestration, carbon-aware scheduling, and financial governance mechanisms can significantly improve energy efficiency and reduce emissions without compromising service quality (Maheshkar 2024; Maheshkar Patent). The study concludes that sustainable data center management requires unified, adaptive, and policy-driven systems that align technical performance with environmental responsibility (Maheshkar 2026; Singh et al. 2026).
Tolulope Barakat (Thu,) studied this question.
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