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Wireless Sensor Network Architecture based on Fog Computing

机译:基于雾计算的无线传感器网络架构

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Wireless Sensor Network (WSN) has been a focus for research in the last years due to the promising technology it embeds. This appears to be the most sustainable technology for environmental sensing whether it's about limited or large-scale monitoring, thanks to the ad-hoc wireless links, scalability and ease of implementation. However, main drawbacks are stemming from the limited capacity of network nodes for data storage, computing and accessing. To overcome these limitations, virtualized resources were appended allowing access to increased storage, processing and user-friendly accessibility. This came as a natural development of the common WSN architectures in the trend of modern concepts emerged with the IoT (Internet of Things) technologies proliferation. Despite the increasing usage of cloud-based WSN monitoring systems, there are still issues due to the drawbacks of cloud computing such as latency and storage costs. This paper discusses the improvements made to a cloud-based WSN architecture by adding a layer of computing at the edge of the network, a method that follows the novel model of analysing and acting on IoT data, entitled Fog Computing. Comparative analytics were performed to prove the improvements achieved through edge of the network computing.
机译:由于无线传感器网络嵌入的技术很有前途,因此近年来一直是研究的重点。由于ad-hoc无线链接,可伸缩性和易于实施,这似乎是最可持续的环境传感技术,无论是有限监视还是大规模监视。但是,主要缺点是由于网络节点用于数据存储,计算和访问的能力有限。为了克服这些限制,虚拟资源被附加,允许访问增加的存储,处理和用户友好的可访问性。随着IoT(物联网)技术的兴起,现代概念的趋势出现,这是通用WSN架构的自然发展。尽管基于云的WSN监视系统的使用越来越多,但是由于云计算的缺点(例如延迟和存储成本)仍然存在一些问题。本文讨论了通过在网络边缘添加一层计算来对基于云的WSN体系结构进行的改进,该方法遵循一种称为雾计算的新颖模型来分析和作用于IoT数据。进行了比较分析,以证明通过网络计算的边缘实现的改进。

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