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 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.