When Mathematical Methods Meet Artificial Intelligence and Mobile Edge Computing
Yuzhu Liang,
Xiaotong Bi,
Ruihan Shen,
Zhengyang He,
Yuqi Wang,
Juntao Xu,
Yao Zhang and
Xinggang Fan ()
Additional contact information
Yuzhu Liang: Advanced Institute of Natural Sciences, Beijing Normal University, Zhuhai 519087, China
Xiaotong Bi: College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310014, China
Ruihan Shen: School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an 710129, China
Zhengyang He: Zhijiang College, Zhejiang University of Technology, Shaoxing 312030, China
Yuqi Wang: College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310014, China
Juntao Xu: College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310014, China
Yao Zhang: School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an 710129, China
Xinggang Fan: Zhijiang College, Zhejiang University of Technology, Shaoxing 312030, China
Mathematics, 2025, vol. 13, issue 11, 1-38
Abstract:
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.
Keywords: mathematical methods; artificial intelligence; mobile edge computing (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:
Downloads: (external link)
https://www.mdpi.com/2227-7390/13/11/1779/pdf (application/pdf)
https://www.mdpi.com/2227-7390/13/11/1779/ (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:13:y:2025:i:11:p:1779-:d:1665382
Access Statistics for this article
Mathematics is currently edited by Ms. Emma He
More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().