基于5G低功耗广域网的智慧城市应用异常检测

José Santos, P. Leroux, T. Wauters, B. Volckaert, F. Turck
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引用次数: 48

摘要

近年来,物联网(IoT)为电信业带来了一系列全新的挑战和机遇。由于许多传感器和日常设备被连接起来,无线网络上的流量呈指数级增长。因此,当前的网络必须适应和应对物联网引入的特定要求。下一代网络系统的一个基本需求是监控物联网应用,特别是那些处理个人健康监测或应急响应服务的应用,这些应用在处理故障或异常事件时具有严格的延迟要求。传统的异常检测方法不适合延迟敏感的物联网应用,因为这些方法受到延迟的显著影响。随着5G网络的到来,通过利用软件定义网络(SDN)、网络功能虚拟化(NFV)和边缘计算等新范式的优势,可扩展、低延迟的异常检测变得可行。本文提出了一种用于智慧城市应用的异常检测解决方案,重点关注低功耗雾计算解决方案,并在安特卫普的物联网城市试验台范围内进行了评估。基于收集的大型数据集,研究了最适合我们智慧城市用例的低功耗广域网(LPWAN)技术。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Anomaly detection for Smart City applications over 5G low power wide area networks
In recent years, the Internet of Things (IoT) has introduced a whole new set of challenges and opportunities in Telecommunications. Traffic over wireless networks has been increasing exponentially since many sensors and everyday devices are being connected. Current networks must therefore adapt to and cope with the specific requirements introduced by IoT. One fundamental need of the next generation networked systems is to monitor IoT applications, especially those dealing with personal health monitoring or emergency response services, which have stringent latency requirements when dealing with malfunctions or unusual events. Traditional anomaly detection approaches are not suitable for delay-sensitive IoT applications since these approaches are significantly impacted by latency. With the advent of 5G networks and by exploiting the advantages of new paradigms, such as Software-Defined Networking (SDN), Network Function Virtualization (NFV) and edge computing, scalable, low-latency anomaly detection becomes feasible. In this paper, an anomaly detection solution for Smart City applications is presented, focusing on low-power Fog Computing solutions and evaluated within the scope of Antwerp's City of Things testbed. Based on a collected large dataset, the most appropriate Low Power Wide Area Network (LPWAN) technologies for our Smart City use case are investigated.
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