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Comparison of Alternative Architectures in Fog Computing

机译:雾计算中替代架构的比较

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Since the proliferation of fog computing, various distributed architectures have been proposed to extend the cloud to the edge of the network. However, so far there exists no study that compares different fog computing architectures, and produces quantitative results in order to examine the efficiency of each architecture for different use cases. Such a study could provide guidelines for selecting an appropriate distributed architecture for fog computing while taking into account the requirements of the final applications.To bridge this gap in the literature, we create a unified system model which is able to represent the basic architectures commonly used for fog computing, i.e., hierarchical and flat. Furthermore, we design algorithms that can be used for creating fog computing systems that follow these architectures, and we perform various experiments that focus on communication latency and bandwidth utilization. Notably, our results show that for applications that do not have a dependency on the cloud, i.e., no resource-demanding tasks are involved, the hierarchical architecture reduces the communication latency by 13% compared to the flat. However, for applications that also include resource-demanding tasks, the flat architecture reduces the communication latency by 16% compared to the hierarchical.
机译:由于雾计算的激增,已经提出了各种分布式体系结构以将云扩展到网络的边缘。但是,到目前为止,还没有研究可以比较不同的雾计算体系结构并产生定量结果,以检查每种体系结构在不同用例下的效率。这样的研究可以在考虑最终应用程序需求的同时为选择合适的分布式雾计算架构提供指导。为了弥补文献中的空白,我们创建了一个统一的系统模型,该模型可以表示常用的基本架构。用于雾计算,即分层和平整。此外,我们设计了可用于创建遵循这些架构的雾计算系统的算法,并且我们进行了专注于通信延迟和带宽利用率的各种实验。值得注意的是,我们的结果表明,对于不依赖云的应用程序(即不涉及资源需求的任务),与平台相比,分层体系结构将通信延迟降低了13%。但是,对于还包括资源需求任务的应用程序,与分层结构相比,扁平化体系结构将通信延迟减少了16%。

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