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Fog computing through public-resource computing and storage

机译:通过公共资源计算和存储进行雾计算

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Fog computing is a model in which data and processing are concentrated on devices at the edge of the network, rather than almost entirely in the cloud. This new paradigm tries to solve the latency and bandwidth issues that the current cloud systems have to deal with, and also addresses the scalability problems caused by the exponential growth of the number of smart devices due to the success of the Internet of Things. In this paper we introduce the idea of using public-resource computing and storage techniques in order to process part of the workload of the current cloud systems so as to avoid saturating the cloud. This idea proposes the use of devices working as participants, which form a data center between the cloud service providers and the end-clients. A participant can be any type of device, from a traditional PC (Personal Computer), to a smartphone or tablet or even a smart TV. We have evaluated two different case studies by simulating the use of participating nodes in video-transfer applications. The results of the simulations demonstrate that public-resource computing and storage can be used to solve the latency and bandwidth issues that affect the current cloud systems. Therefore, our results represent a feasible solution for applications that process or store public data.
机译:雾计算是一种模型,其中数据和处理集中在网络边缘的设备上,而不是几乎全部集中在云中。这个新范例试图解决当前云系统必须处理的延迟和带宽问题,并且还解决了由于物联网的成功而导致智能设备数量呈指数增长所导致的可伸缩性问题。在本文中,我们介绍了使用公共资源计算和存储技术的想法,以便处理当前云系统的部分工作负载,从而避免云饱和。这个想法建议使用充当参与者的设备,这些设备在云服务提供商和最终客户端之间形成数据中心。参与者可以是任何类型的设备,从传统的PC(个人计算机)到智能手机或平板电脑,甚至是智能电视。通过模拟视频传输应用程序中参与节点的使用,我们评估了两个不同的案例研究。仿真结果表明,公共资源计算和存储可用于解决影响当前云系统的延迟和带宽问题。因此,我们的结果为处理或存储公共数据的应用程序提供了可行的解决方案。

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