AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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This methodology proposes a generic architecture of MAS that deals with distributed decision-making that includes agent perception, local reasoning, coordination and global optimization.
The experimental performance proves that data science-based automation is much more efficient than the conventional approaches to automation concerning energy optimization and prediction of user behavior and validate the fact that the combination of IoT and data science forms a strong venue of the future smart houses.
This paper explores the transformative potential of Artificial Intelligence (AI)-driven cloud solutions in modernizing enterprise architecture, with a focus on integrating DevOps and DataOps methodologies to achieve scalability.
This paper entails a detailed analysis of distributed database in the contemporary computer use and discusses the architectural concepts, design techniques, data dispersion strategies, and consistency models and techniques of dealing with transaction in a distributed database system.
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