基于数字孪生的物联网系统数据采集的命名数据网络(NDN)

Hengshuo Liang, Cheng Qian, Chao Lu, Lauren Burgess, John Mulo, Wei Yu
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引用次数: 0

摘要

随着数字孪生(DT)作为一种提供物联网(IoT)和数据分析之间集成的方式的兴起和越来越多的关注,也需要考虑如何应对其挑战。为了应对这些挑战,命名数据网络(NDN)可能是一种解决方案。NDN由于其在传统TCP/IP互联网架构上的进步而越来越受欢迎。在本文中,我们的方法从利用基于ndn的DT架构进行数据管理的框架开始。然后,我们设计了两个场景,重点关注小型和大规模模拟基于ndn的DT架构中的数据查询性能。根据设计的场景,我们对数据查询和DT性能进行性能评估,以调查性能差距,并确定是否需要采取行动。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Named Data Networking (NDN) for Data Collection of Digital Twins-based IoT Systems
With the rise and growing attention on Digital Twins (DT) as a way to provide integration between the Internet of Things (IoT) and data analytics, so does the need to consider how to address its challenges. To deal with these challenges, Named Data Networking (NDN) can be a possible solution. NDN has been rising in popularity due to its advancements over the traditional TCP/IP Internet architecture. In this paper, our approach begins with the framework that leverages an NDN-based DT architecture for data management. We then design two scenarios that focus on the performance of data querying in a small and large-scale simulated NDN-based DT architecture. Based on the designed scenarios, we conduct the performance evaluation of data query and DT performance to investigate the performance gap and determine whether an action needs to be taken.
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