In this emerging world of connected devices, the need for more computing devices with a focus on delay-sensitive application is critical. In this paper, we propose a priority-queue based Fog computing architecture combined with dynamic scalability of fog devices, which not only reduces the delay experienced by delay-sensitive tasks by categorizing the delay-sensitive and delay-insensitive tasks, but also dynamically allocates the fog devices within the network depending upon the computation load for reducing the power consumption. The results show that the proposed algorithm is able to achieve a significantly lower delay for both delay-sensitive and -insensitive tasks when compared with other related schemes with a 14.5% lower power consumption.

中文翻译：

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基于优先级队列的动态缩放在雾计算中实现高效资源分配

在这个连接设备的新兴世界中，需要更多专注于延迟敏感应用程序的计算设备是至关重要的。在本文中，我们提出了一种基于优先队列的雾计算架构，结合雾设备的动态可扩展性，它不仅通过对延迟敏感和延迟不敏感任务进行分类来减少延迟敏感任务所经历的延迟，而且还动态分配网络内的雾设备取决于计算负载以降低功耗。结果表明，与其他相关方案相比，所提出的算法对于延迟敏感和不敏感任务都能够实现显着更低的延迟，功耗降低 14.5%。