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M. Meiyi, E. Bartocci, E. Lifland, J. Stankovic, L. Feng:
"SaSTL: Spatial Aggregation Signal Temporal Logic for Runtime Monitoring in Smart Cities";
Talk: Proc. of ICCPS 2020: the ACM/IEEE 11th International Conference on Cyber-Physical Systems, Sydney, Australia, Australia; 2020-04-21 - 2020-04-25; in: "Proc. of ICCPS 2020: the ACM/IEEE 11th International Conference on Cyber-Physical Systems", IEEE, (2020), ISBN: 978-1-7281-5502-9; 51 - 62.

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.

http://dx.doi.org/10.1109/ICCPS48487.2020.00013