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A hybrid approach to scheduling real-time loT workflows in fog and cloud environments

机译:一种混合方法来安排雾和云环境中的实时批次工作流程

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摘要

In this paper, we propose a hybrid fog and cloud-aware heuristic for the dynamic scheduling of multiple real-time Internet of Things (IoT) workflows in a three-tiered architecture. In contrast to traditional approaches where the main processing of IoT jobs is performed in the fog layer, our approach attempts to schedule computationally demanding tasks with low communication requirements in the cloud and communication intensive tasks with low computational demands in the fog, utilizing possible gaps in the schedule of the fog and cloud virtual machines. Furthermore, during the scheduling process, our approach takes into account the communication cost incurred by the transfer of data from the sensors and devices in the IoT layer to the fog layer. The performance of the proposed heuristic is evaluated and compared via simulation to a baseline cloud-unaware strategy, under different cases of workload. The simulation results reveal that the proposed scheduling heuristic provides on average 76.69% lower deadline miss ratio, compared to the baseline policy. However, this is achieved at a significant monetary cost, due to the usage of cloud resources.
机译:在本文中,我们提出了一种混合雾和云感知启发式,用于三层架构中的多个实时内容的多次实时互联网(物联网)工作流程的动态调度。与传统方法相比,在雾层中执行了IoT作业的主要处理,我们的方法试图在云中的云和通信密集型任务中具有低通信需求的计算要求,利用可能的空白雾和云虚拟机的时间表。此外,在调度过程中,我们的方法考虑了通过从传感器和IOT层中的数据传输到雾层的数据产生的通信成本。在不同的工作量的不同情况下,通过模拟评估和比较拟议启发式的性能。仿真结果表明,与基线政策相比,建议的调度启发式提供了平均较低的截止日期比例比率为76.69%。然而,由于云资源的使用,这是以重大的货币成本实现的。

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