A Review of Resource Allocation for Maximizing Performance of IoT Systems | Zendy

Mahdi Safaei Yaraziz | Zendy; Richard Hill | Zendy

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A Review of Resource Allocation for Maximizing Performance of IoT Systems

Author(s) -

Mahdi Safaei Yaraziz,

Richard Hill

Publication year - 2025

Publication title -

ieee access

Language(s) - English

Resource type - Magazines

SCImago Journal Rank - 0.587

H-Index - 127

eISSN - 2169-3536

DOI - 10.1109/access.2025.3576716

Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation

Resource allocation is critical for maximizing the performance of Internet of Things (IoT) systems, in which devices with limited resources work together to complete diverse tasks. This paper provides a detailed overview of existing resource management solutions in IoT contexts, with a particular emphasis on AI techniques, heuristic/metaheuristic, 5G/6G, digital twins, and blockchain. We evaluate the potential advantages and limitations of several resource allocation techniques and frameworks suggested in the literature. Our findings emphasize the potential of advanced AI and decentralized approaches to solving critical difficulties in IoT systems, including security and privacy preservation, communication overhead reduction, energy consumption, real-time performance, and scalability enhancement. Furthermore, the ramifications of these discoveries were examined, as well as potential possibilities for future research in this vital field of study.

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