Experimental Characterization of Latency in Distributed IoT Systems with Cloud Fog Offloading

2019 15th IEEE International Workshop on Factory Communication Systems (WFCS) Pub Date : 2019-05-01 DOI:10.1109/WFCS.2019.8757960

Tania Taami, Silvia Krug, M. O’nils

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引用次数: 19

Abstract

The Internet of Things (IoT) enables users to gather and analyze data from a large number of devices. Knowledge obtained by these systems is valuable in order to understand, control, and enhance the monitored process. The mass of information to process leads however to new challenges related to required resources for both data processing and data transportation. Two critical metrics are latency and consumed energy to complete a given task. Both metrics might be exceed if all processing is done locally at the sensor device level. Cloud and Fog computing concepts can help to mitigate this effect. However, using such offloading concepts add complexity and overhead to the system. In this paper, we study the latency for processing and communication tasks in a distributed IoT systems with respect to cloud or fog offloading and derive characteristic cost functions for the studied tasks. Our results give valuable insights into the tradeoffs and constraint within our example scenario. The developed characterization methodology can however be applied to any kind of IoT system and thus allowing more general analysis.

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云雾卸载分布式物联网系统延迟的实验表征

物联网(IoT)使用户能够从大量设备中收集和分析数据。这些系统所获得的知识对于理解、控制和加强被监视的过程是有价值的。然而，需要处理的大量信息带来了与数据处理和数据传输所需资源相关的新挑战。两个关键指标是延迟和完成给定任务所消耗的能量。如果所有处理都在传感器设备级别本地完成，则可能超过这两个指标。云和雾计算概念可以帮助减轻这种影响。然而，使用这样的卸载概念会增加系统的复杂性和开销。在本文中，我们研究了分布式物联网系统中关于云或雾卸载的处理和通信任务的延迟，并为所研究的任务导出了特征成本函数。我们的结果为示例场景中的权衡和约束提供了有价值的见解。然而，开发的表征方法可以应用于任何类型的物联网系统，从而允许更一般的分析。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2019 15th IEEE International Workshop on Factory Communication Systems (WFCS)

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