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首页> 外文期刊>Annales des Telecommunications >Placing it right!: optimizing energy, processing, and transport in Edge-Fog clouds
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Placing it right!: optimizing energy, processing, and transport in Edge-Fog clouds

机译:正确处理!:优化Edge-Fog云中的能源,处理和传输

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摘要

In recent years, applications such as Internet-of-Things has proliferated the Internet to a great extent. Such applications derive data from a significant number of smart sensors sensing information from the environment. Due to an extensive data footprint, the demand for cloud services to process this data has also increased. However, traditional centralized cloud model requires offloading data from these sensors over a network which induces significant network delay on these applications. Several architectural abstractions of cloud, such as Fog and Edge, have been proposed to localize some of the processing near the sensors and away from the central cloud servers. In this paper, we propose Edge-Fog cloud which distributes task processing on the participating cloud resources in the network. We develop the Least Processing Cost First (LPCF) method for assigning the processing tasks to nodes which provide the optimal processing time and near-optimal networking costs. We further provide an energy-efficient variant of LPCF, i.e., eLPCF algorithm, which optimizes energy usage while calculating task deployment in Edge-Fog cloud. We evaluate both LPCF and eLPCF in a variety of scenarios and demonstrate its effectiveness in finding the processing task assignments.
机译:近年来,诸如物联网之类的应用程序在很大程度上扩展了Internet。这样的应用程序从大量的智能传感器中获取数据,这些传感器从环境中感应信息。由于广泛的数据覆盖,对云服务来处理该数据的需求也增加了。但是,传统的集中式云模型需要通过网络从这些传感器分流数据,这会在这些应用程序上引起明显的网络延迟。已经提出了几种云的体系结构抽象,例如Fog和Edge,以将一些处理本地化在传感器附近和中央云服务器之外。在本文中,我们提出了Edge-Fog云,它在网络中参与的云资源上分配任务处理。我们开发了“最低优先处理成本”(LPCF)方法,用于将处理任务分配给节点,以提供最佳处理时间和近乎最佳的网络成本。我们还提供了LPCF的节能型,即eLPCF算法,可在计算Edge-Fog云中的任务部署时优化能耗。我们在各种情况下评估LPCF和eLPCF,并证明其在查找处理任务分配中的有效性。

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