AI-Driven Adaptive Algorithms for Large-Scale Sustainable Computing Systems
Keywords:
AI-Driven Algorithms, Adaptive Systems, Sustainable Computing, Large-Scale Systems, Energy Efficiency,, Resource Optimization,, Intelligent InfrastructureAbstract
AI-driven adaptive algorithms have emerged as a foundational approach for managing large-scale sustainable computing systems. These algorithms enable systems to dynamically optimize resource utilization, energy efficiency, and performance under varying workloads and environmental constraints. In the current technological context, large-scale computing infrastructures such as data centers, cloud platforms, and distributed cyber-physical systems increasingly rely on intelligent adaptability to meet sustainability objectives. This paper presents a structured analysis of AI-driven adaptive algorithms, emphasizing architectural principles, operational mechanisms, and sustainability outcomes. The discussion integrates system-level perspectives with algorithmic intelligence to highlight how adaptive learning, real-time feedback, and autonomous decision-making collectively enhance sustainable computing.
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Copyright (c) 2026 Thiago Gabriel, Samuel Charles (Author)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
