Auction-based Adaptive Resource Allocation Optimization in Dense IoT Networks
<|reference_start|>Auction-based Adaptive Resource Allocation Optimization in Dense IoT Networks: The rapid pervasivity of the Internet of Things (IoT) calls for an autonomous and efficient resource management framework to seamlessly register and discover facilities and services. Cloud-Fog-Automation (CFA) standards provide a robust foundation for multi-tiered wireless architectures, enhancing cyber-physical system performance with advanced abstractions. This work is for resource allocation optimization in IoT networks, particularly in power management and time-frequency spreading techniques, ensuring deterministic connectivity, networked computing, and intelligent control systems. Auction game theory is pivotal in managing resource allocation in densely populated, high-demand IoT networks. By employing sealed-bid auctions based on Bayesian game theory, the uncertainties in individual hypotheses and channel states among IoT entities are effectively mitigated. A novel dispersion metric optimization further enhances the coordination of layer-specific IoT uplinks, enabling ultra-reliable, low-latency (URLLC) communication. Numerical results demonstrate the superior performance of this resilient architecture, achieving fair resource allocation with minimal power consumption and robust performance in unsecured scenarios.<|reference_end|>
@article{wickramasinghe2024auction-based,
    title={Auction-based Adaptive Resource Allocation Optimization in Dense IoT
  Networks},
    author={Nirmal D. Wickramasinghe, John Dooley, Dirk Pesch, Indrakshi Dey},
    journal={arXiv preprint arXiv:2409.17843},
    year={2024},
    archivePrefix={arXiv},
    eprint={2409.17843},
    primaryClass={cs.GT}
}