AI-POWERED SOLUTIONS FOR ENHANCING ENERGY EFFICIENCY AND RESOURCE MANAGEMENT IN MODERN DATA CENTERS
Keywords:
Artificial Intelligence (AI), I Powered Solutions, Predictive Analytics, Resource Optimization, Energy EfficiencyAbstract
Data centers are integral to the digital economy, but their rapid growth presents increasing challenges, particularly in terms of energy consumption and operational complexity. This paper explores the potential of artificial intelligence (AI) techniques to enhance energy efficiency and optimize resource utilization in contemporary data centers. Key areas of focus include workload forecasting, dynamic resource allocation, and optimizing cooling system performance. By leveraging advanced AI methodologies such as reinforcement learning, predictive analytics, and neural network models, this research aims to address two primary objectives: reducing operational costs and minimizing the environmental impact of data centers. The AI-driven solutions are evaluated in both virtual and real-world scenarios, with performance metrics compared to traditional heuristic-based algorithms. The findings offer practical insights for the design and deployment of more efficient, sustainable data centers in an increasingly computationally demanding environment.
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Copyright (c) 2025 Sai Prakash Narasingu (Author)
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