In Internet of Things (IoT) data processing, cloud computing alone does not suffice due to latency constraints, bandwidth limitations, and privacy concerns. By introducing intermediary nodes closer to the edge of the network that offer compute services in proximity to IoT devices, fog computing can reduce network strain and high access latency to application services. While this is the only viable approach to enable efficient IoT applications, the issue of component placement among cloud and intermediary nodes in the fog adds a new dimension to system design. State-of-the-art solutions to this issue rely on simulation or solving a formalized assignment problem through heuristics only, which both have their drawbacks. In this article, we present a five-step process for designing practical fog-based IoT applications that combines best practices, simulation, and testbed analysis to converge towards an efficient system architecture. We then apply this process in a smart factory case study. By deploying filtered options to a physical testbed, we show that each step of our process converges towards more efficient application designs.

中文翻译：

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从零到雾：基于雾的物联网应用的高效工程

在物联网 (IoT) 数据处理中，由于延迟限制、带宽限制和隐私问题，仅靠云计算是不够的。通过在靠近网络边缘的地方引入中间节点，在物联网设备附近提供计算服务，雾计算可以减少网络压力和对应用程序服务的高访问延迟。虽然这是实现高效物联网应用的唯一可行方法，但雾中云和中间节点之间的组件放置问题为系统设计增加了一个新维度。该问题的最新解决方案依赖于模拟或仅通过启发式方法解决形式化分配问题，这两者都有其缺点。在本文中，我们介绍了设计实用的基于雾的物联网应用程序的五步过程，这些应用程序结合了最佳实践，仿真和测试台分析以收敛于高效的系统架构。然后，我们将这个过程应用到智能工厂案例研究中。通过将过滤选项部署到物理测试平台，我们表明我们流程的每一步都朝着更高效的应用程序设计收敛。