Smart Transportation Delay and Resiliency Testbed Based on Information Flow of Things Middleware

J. P. Talusan, F. Tiausas, K. Yasumoto, Michael Wilbur, Geoffrey Pettet, A. Dubey, Shameek Bhattacharjee
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引用次数: 4

Abstract

Edge and Fog computing paradigms are used to process big data generated by the increasing number of IoT devices. These paradigms have enabled cities to become smarter in various aspects via real-time data-driven applications. While these have addressed some flaws of cloud computing some challenges remain particularly in terms of privacy and security. We create a testbed based on a distributed processing platform called the Information flow of Things (IFoT) middleware. We briefly describe a decentralized traffic speed query and routing service implemented on this framework testbed. We configure the testbed to test countermeasure systems that aim to address the security challenges faced by prior paradigms. Using this testbed, we investigate a novel decentralized anomaly detection approach for time-sensitive distributed smart transportation systems.
基于信息流中间件的智能交通延迟与弹性试验台
边缘和雾计算范式用于处理越来越多的物联网设备产生的大数据。这些范例通过实时数据驱动的应用程序使城市在各个方面变得更加智能。虽然这些解决了云计算的一些缺陷,但仍然存在一些挑战,特别是在隐私和安全方面。我们创建了一个基于分布式处理平台的测试平台,该平台称为信息流(IFoT)中间件。简要介绍了在该框架测试平台上实现的分散流量速度查询和路由服务。我们配置测试平台来测试旨在解决先前范例所面临的安全挑战的对策系统。利用该测试平台,我们研究了一种用于时间敏感分布式智能交通系统的新型分散异常检测方法。
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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