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When Mathematical Methods Meet Artificial Intelligence and Mobile Edge Computing

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Publicado en:Mathematics vol. 13, no. 11 (2025), p. 1779
Autor principal: Liang Yuzhu
Otros Autores: Bi Xiaotong, Shen Ruihan, He Zhengyang, Wang, Yuqi, Xu, Juntao, Zhang, Yao, Fan Xinggang
Publicado:
MDPI AG
Materias:
Smart cities
Machine learning
Artificial intelligence
Edge computing
Adaptability
Intelligent systems
Optimization
Decision making
Mobile computing
Taxonomy
Data science
Data integration
Algorithms
Utility computing
Real time
Cloud computing
Queuing theory
Internet of Things
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Resumen:The integration of mathematical methods with artificial intelligence (AI) and mobile edge computing (MEC) has emerged as a promising research direction to address the growing complexity of intelligent distributed systems. To chart the landscape of this interdisciplinary field, we first examine recent surveys that primarily focus on architectural designs, learning paradigms, and system-level deployments in edge AI. However, these studies largely overlook the theoretical foundations essential for ensuring reliability, interpretability, and efficiency. This paper fills this gap by conducting a comprehensive survey of mathematical methods and analyzing their applications in AI-enabled MEC systems. We focus on addressing three key challenges: heterogeneous data integration, real-time optimization, and computational scalability. We summarize state-of-the-art schemes to address these challenges and identify several open issues and promising future research directions.
ISSN:2227-7390
DOI:10.3390/math13111779
Fuente:Engineering Database