Information & Computing Lab, AtlantTIC Research Center, Universidade de Vigo, 36310 Vigo, Spain.
SAMOVAR (Services répartis, Architectures, MOdélisation, Validation, Administration des Réseaux), Télécom SudParis, CNRS, Université Paris-Saclay, 91000 Évry, France.
Sensors (Basel). 2018 Dec 29;19(1):104. doi: 10.3390/s19010104.
Since smart cities aim at becoming self-monitoring and self-response systems, their deployment relies on close resource monitoring through large-scale urban sensing. The subsequent gathering of massive amounts of data makes essential the development of event-filtering mechanisms that enable the selection of what is relevant and trustworthy. Due to the rise of mobile event producers, location information has become a valuable filtering criterion, as it not only offers extra information on the described event, but also enhances trust in the producer. Implementing mechanisms that validate the quality of location information becomes then imperative. The lack of such strategies in cloud architectures compels the adoption of new communication schemes for Internet of Things (IoT)-based urban services. To serve the demand for location verification in urban event-based systems (DEBS), we have designed three different fog architectures that combine proximity and cloud communication. We have used network simulations with realistic urban traces to prove that the three of them can correctly identify between 73% and 100% of false location claims.
由于智慧城市旨在成为自我监测和自我响应的系统，因此它们的部署依赖于通过大规模城市感测进行密切的资源监测。随后收集的大量数据使得必须开发事件过滤机制，以便选择相关且值得信任的内容。由于移动事件生成器的兴起，位置信息已成为有价值的筛选标准，因为它不仅提供了有关描述事件的其他信息，而且还增强了对生成器的信任。然后，实施验证位置信息质量的机制变得势在必行。云架构中缺乏此类策略，迫使采用新的通信方案来为基于物联网的城市服务。为了满足城市基于事件的系统（DEBS）中位置验证的需求，我们设计了三种不同的雾架构，这些架构结合了临近性和云通信。我们使用具有现实城市轨迹的网络模拟来证明，这三种架构都可以正确识别 73%到 100%的虚假位置声称。
