Cloud- and fog-based networks are promising paradigms for vehicular and mobile networks. Fog radio access networks (F-RANs), in particular, can offload computation tasks to the network edge (i.e., in the fog) and reduce latency. Artificial intelligence (AI) techniques can be used in F-RANs to achieve, for example, enhanced energy efficiency and increased throughput. Nonetheless, the appropriate technique selection must consider the different time granularities at which decision making occurs in F-RANs.

中文翻译：

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人工智能驱动的雾无线接入网络：考虑不同时间粒度的综合决策


基于云和雾的网络是车辆和移动网络的有前途的范例。特别是，雾无线接入网络（F-RAN）可以将计算任务卸载到网络边缘（即在雾中）并减少延迟。人工智能 (AI) 技术可用于 F-RAN，以实现提高能源效率和增加吞吐量等目的。尽管如此，适当的技术选择必须考虑 F-RAN 中决策发生的不同时间粒度。