MoonLight: A Lightweight Tool for Monitoring Spatio-Temporal Properties

Bartocci, Ezio; Bortolussi, Luca; Loreti, Michele; Nenzi, Laura; Silvetti, Simone

doi:10.1007/978-3-030-60508-7_23

Cited by 20 publications

(25 citation statements)

References 31 publications

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“…We use the MoonLight tool (developed to monitor temporal and spatial-temporal properties of Cyber-Physical systems) [113] to find a counterexample for ϕ AT 1 . Since we need robustness value for solving the optimization problem, we consider the quantitative semantics (or the minmax semantics) in this work.…”

Section: Simulation Resultsmentioning

confidence: 99%

Blood Coagulation Algorithm: A Novel Bio-Inspired Meta-Heuristic Algorithm for Global Optimization

Yadav

2021

Mathematics

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This paper introduces a novel population-based bio-inspired meta-heuristic optimization algorithm, called Blood Coagulation Algorithm (BCA). BCA derives inspiration from the process of blood coagulation in the human body. The underlying concepts and ideas behind the proposed algorithm are the cooperative behavior of thrombocytes and their intelligent strategy of clot formation. These behaviors are modeled and utilized to underscore intensification and diversification in a given search space. A comparison with various state-of-the-art meta-heuristic algorithms over a test suite of 23 renowned benchmark functions reflects the efficiency of BCA. An extensive investigation is conducted to analyze the performance, convergence behavior and computational complexity of BCA. The comparative study and statistical test analysis demonstrate that BCA offers very competitive and statistically significant results compared to other eminent meta-heuristic algorithms. Experimental results also show the consistent performance of BCA in high dimensional search spaces. Furthermore, we demonstrate the applicability of BCA on real-world applications by solving several real-life engineering problems.

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Section: Simulation Resultsmentioning

confidence: 99%

Blood Coagulation Algorithm: A Novel Bio-Inspired Meta-Heuristic Algorithm for Global Optimization

Yadav

2021

Mathematics

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“…The SSTL semantics operates on a weighted undirected graph, where the weight on each edge represents the distance between two nodes. The Spatial Temporal Reach and Escape Logic (STREL) [13], [14] generalizes SSTL, by introducing two new spatial operators, (reach and escape), which are able to express the same spatial operators of SSTL. Furthermore, while SSTL can be applied only on static weight undirected graphs, STREL can be applied also to dynamic networks.…”

Section: Ar5mentioning

confidence: 99%

A Novel Spatial–Temporal Specification-Based Monitoring System for Smart Cities

Bartocci

Lifland

et al. 2021

IEEE Internet Things J.

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With the development of the Internet of Things, millions of sensors are being deployed in cities to collect realtime data. This leads to a need for checking city states against city requirements at runtime. In this paper, we develop a novel spatial-temporal specification-based monitoring system for smart cities. We first describe a study of over 1,000 smart city requirements, some of which cannot be specified using existing logic such as Signal Temporal Logic (STL) and its variants. To tackle this limitation, we develop SaSTL-a novel Spatial Aggregation Signal Temporal Logic-for the efficient runtime monitoring of safety and performance requirements in smart cities. 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 define Boolean and quantitative semantics for SaSTL in support of the analysis of city performance across different periods and locations. 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). Additionally, we build a SaSTL-based monitoring tool to support decision making of different stakeholders to specify and runtime monitor their requirements in smart cities. We evaluate our SaSTL monitor by applying it to three case studies with large-scale real city sensing data (e.g., up to 10,000 sensors in one study). 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 improves the safety and performance of smart cities via simulated experiments.

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“…Breach monitor has been measured via the reference implementation as a Simulink model, while Moonlight is implemented as a Java program. Table 1 The interesting insight of the comparison is the fact that, while our in-order implementation provides reliably faster performances (note that the offline version of Moonlight had already shown better performance than Breach in [2]), the penalty that comes from not assuming ordered inputs grows substantially with the increase of the input size, as this requires longer searches in the output signal, to find the spot where the update should be applied. Nevertheless, the biggest sample size we considered is quite extreme (ten thousand randomly-shuffled samples), yet the execution time (4.489 ms/sample on average) is way smaller than the sampling time (0.1 s), which therefore makes it reasonable for most real-time scenarios.…”

Section: Online Comparison: Abstract Fuel Controlmentioning

confidence: 99%

“…STREL extends the Signal Temporal Logic (STL) [25] with the reach and escape operators that generalizes the somewhere, everywhere and surronded spatial modalities, simplifying the monitoring that can be computed locally with respect to each node. However, the original work on STREL [1,2] provides only an offline monitoring algorithm. In contrast we present here the first online monitoring algorithm for STREL and in general for spatio-temporal monitoring.…”

Section: Introductionmentioning

confidence: 99%

Online Monitoring of Spatio-Temporal Properties for Imprecise Signals

Visconti¹,

Bartocci²,

Loreti³

et al. 2021

Preprint

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From biological systems to cyber-physical systems, monitoring the behavior of such dynamical systems often requires to reason about complex spatio-temporal properties of physical and/or computational entities that are dynamically interconnected and arranged in a particular spatial configuration. Spatio-Temporal Reach and Escape Logic (STREL) is a recent logic-based formal language designed to specify and to reason about spatio-temporal properties. STREL considers each system's entity as a node of a dynamic weighted graph representing their spatial arrangement. Each node generates a set of mixed-analog signals describing the evolution over time of computational and physical quantities characterising the node's behavior. While there are offline algorithms available for monitoring STREL specifications over logged simulation traces, here we investigate for the first time an online algorithm enabling the runtime verification during the system's execution or simulation. Our approach extends the original framework by considering imprecise signals and by enhancing the logics' semantics with the possibility to express partial guarantees about the conformance of the system's behavior with its specification. Finally, we demonstrate our approach in a real-world environmental monitoring case study. CCS CONCEPTS• Theory of computation → Logic and verification; Modal and temporal logics; • Software and its engineering → Abstraction, modeling and modularity.

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MoonLight: A Lightweight Tool for Monitoring Spatio-Temporal Properties

Cited by 20 publications

References 31 publications

Blood Coagulation Algorithm: A Novel Bio-Inspired Meta-Heuristic Algorithm for Global Optimization

Blood Coagulation Algorithm: A Novel Bio-Inspired Meta-Heuristic Algorithm for Global Optimization

A Novel Spatial–Temporal Specification-Based Monitoring System for Smart Cities

Online Monitoring of Spatio-Temporal Properties for Imprecise Signals

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