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在真实环境中检验雾辅助、以云为中心的物联网的性能。

Examining the Performance of Fog-Aided, Cloud-Centered IoT in a Real-World Environment.

机构信息

Department of Computer Science, The University of Idaho, Moscow, ID 83844, USA.

Department of Computer Science, Majmaah University, Al-Majmaah 11952, Saudi Arabia.

出版信息

Sensors (Basel). 2021 Oct 20;21(21):6950. doi: 10.3390/s21216950.

Abstract

The fog layer provides substantial benefits in cloud-based IoT applications because it can serve as an aggregation layer and it moves the computation resources nearer to the IoT devices; however, it is important to ensure adequate performance is achieved in such applications, as the devices usually communicate frequently and authenticate with the cloud. This can cause performance and availability issues, which can be dangerous in critical applications such as in the healthcare sector. In this paper, we analyze the efficacy of the fog layer in different architectures in a real-world environment by examining performance metrics for the cloud and fog layers using different numbers of IoT devices. We also implement the fog layer using two methods to determine whether different fog implementation frameworks can affect the performance. The results show that including a fog layer with semi-heavyweight computation capability results in higher capital costs, although the in the long run resources, time, and money are saved. This study can serve as a reference for fundamental fog computing concepts. It can also be used to walk practitioners through different implementation frameworks of fog-aided IoT and to show tradeoffs in order to inform when to use each implementation framework based on one's objectives.

摘要

雾计算层在基于云的物联网应用中具有重要意义,因为它可以作为聚合层,将计算资源更接近物联网设备;然而,在这些应用中确保实现足够的性能是非常重要的,因为设备通常会频繁地与云进行通信和身份验证。这可能会导致性能和可用性问题,在医疗等关键应用领域可能会非常危险。在本文中,我们通过使用不同数量的物联网设备来检查云层和雾层的性能指标,分析了真实环境中不同架构中雾计算层的效果。我们还使用两种方法实现了雾计算层,以确定不同的雾计算实现框架是否会影响性能。结果表明,虽然包含具有半重量级计算能力的雾计算层会导致更高的资本成本,但从长远来看,资源、时间和资金都会得到节省。本研究可以作为雾计算基本概念的参考,也可以帮助从业者了解雾辅助物联网的不同实现框架,并展示权衡取舍,以便根据目标告知何时使用每个实现框架。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a08b/8587892/52059177f0f8/sensors-21-06950-g001.jpg

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