A Review of Resource Allocation for Maximizing Performance of IoT Systems

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 em...

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Main Authors: Mahdi Safaei Yaraziz, Richard Hill
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/11023604/
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author Mahdi Safaei Yaraziz
Richard Hill
author_facet Mahdi Safaei Yaraziz
Richard Hill
author_sort Mahdi Safaei Yaraziz
collection DOAJ
description 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 approaches, 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 illustrate 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 improvement, 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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spelling doaj-art-169763e83ad5464ca1e71e66ca3d0e792025-08-20T03:21:00ZengIEEEIEEE Access2169-35362025-01-0113984269845110.1109/ACCESS.2025.357671611023604A Review of Resource Allocation for Maximizing Performance of IoT SystemsMahdi Safaei Yaraziz0https://orcid.org/0000-0002-1675-3619Richard Hill1https://orcid.org/0000-0003-0105-7730Department of Computer Science, University of Huddersfield, Huddersfield, U.K.Department of Computer Science, University of Huddersfield, Huddersfield, U.K.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 approaches, 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 illustrate 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 improvement, 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.https://ieeexplore.ieee.org/document/11023604/Resource allocationquality of serviceresource managementInternet of Thingsartificial intelligence
spellingShingle Mahdi Safaei Yaraziz
Richard Hill
A Review of Resource Allocation for Maximizing Performance of IoT Systems
IEEE Access
Resource allocation
quality of service
resource management
Internet of Things
artificial intelligence
title A Review of Resource Allocation for Maximizing Performance of IoT Systems
title_full A Review of Resource Allocation for Maximizing Performance of IoT Systems
title_fullStr A Review of Resource Allocation for Maximizing Performance of IoT Systems
title_full_unstemmed A Review of Resource Allocation for Maximizing Performance of IoT Systems
title_short A Review of Resource Allocation for Maximizing Performance of IoT Systems
title_sort review of resource allocation for maximizing performance of iot systems
topic Resource allocation
quality of service
resource management
Internet of Things
artificial intelligence
url https://ieeexplore.ieee.org/document/11023604/
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