SaSTL: Spatial Aggregation Signal Temporal Logic for Runtime Monitoring in Smart Cities

Meiyi Ma, E. Bartocci, Eli Lifland, J. Stankovic, Lu Feng
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引用次数: 19

Abstract

We present SaSTL—a novel Spatial Aggregation Signal Temporal Logic—for the efficient runtime monitoring of safety and performance requirements in smart cities. We first describe a study of over 1,000 smart city requirements, some of which can not be specified using existing logic such as Signal Temporal Logic (STL) and its variants. To tackle this limitation, we develop two new logical operators in SaSTL to augment STL for expressing spatial aggregation and spatial counting characteristics that are commonly found in real city requirements. We also develop efficient monitoring algorithms that can check a SaSTL requirement in parallel over multiple data streams (e.g., generated by multiple sensors distributed spatially in a city). We evaluate our SaSTL monitor by applying to two case studies with large-scale real city sensing data (e.g., up to 10,000 sensors in one requirement). The results show that SaSTL has a much higher coverage expressiveness than other spatial-temporal logics, and with a significant reduction of computation time for monitoring requirements. We also demonstrate that the SaSTL monitor can help improve the safety and performance of smart cities via simulated experiments.
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面向智慧城市运行监控的空间聚合信号时序逻辑
我们提出了一种新的空间聚合信号时间逻辑,用于智能城市安全和性能要求的有效运行时监控。我们首先描述了一项针对1000多个智慧城市需求的研究,其中一些需求无法使用现有逻辑(如信号时序逻辑(STL)及其变体)来指定。为了解决这一限制,我们在SaSTL中开发了两个新的逻辑运算符来增强STL,以表达在实际城市需求中常见的空间聚合和空间计数特征。我们还开发了有效的监控算法,可以在多个数据流(例如,由分布在城市空间中的多个传感器生成)上并行检查SaSTL要求。我们通过应用两个具有大规模真实城市传感数据的案例研究来评估我们的SaSTL监视器(例如,在一个需求中多达10,000个传感器)。结果表明,SaSTL具有比其他时空逻辑更高的覆盖表达能力,并且显著减少了监测需求的计算时间。我们还通过模拟实验证明了SaSTL监测器可以帮助提高智慧城市的安全性和性能。
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