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.

翻译：物联网（IoT）的快速普及要求一种自主高效的资源管理框架，以实现设施与服务的无缝注册与发现。云-雾-自动化（CFA）标准为多层无线架构提供了坚实基础，通过高级抽象增强了信息物理系统的性能。本研究致力于物联网网络中的资源分配优化，特别是在功率管理和时频扩展技术方面，以确保确定性连接、网络化计算和智能控制系统。拍卖博弈论在管理高密度、高需求物联网网络中的资源分配方面至关重要。通过采用基于贝叶斯博弈论的密封投标拍卖，物联网实体间个体假设与信道状态的不确定性得到了有效缓解。一种新颖的弥散度量优化进一步增强了特定层级物联网上行链路的协调能力，实现了超可靠、低时延（URLLC）通信。数值结果表明，该弹性架构具有优越性能，能够在非安全场景中以最小功耗实现公平的资源分配和鲁棒的性能。