Real-Time Simulation Support for Runtime Verification of Cyber-Physical Systems

Author:

Zheng Xi1ORCID,Julien Christine2,Chen Hongxu3,Podorozhny Rodion4,Cassez Franck5

Affiliation:

1. Deakin University, VIC, Australia

2. The University of Texas at Austin, TX, USA

3. Tsinghua University, Beijing, China

4. Texas State University, USA

5. Macquarie University, Sydney, Australia

Abstract

In Cyber-Physical Systems (CPS), cyber and physical components must work seamlessly in tandem. Runtime verification of CPS is essential yet very difficult, due to deployment environments that are expensive, dangerous, or simply impossible to use for verification tasks. A key enabling factor of runtime verification of CPS is the ability to integrate real-time simulations of portions of the CPS into live running systems. We propose a verification approach that allows CPS application developers to opportunistically leverage real-time simulation to support runtime verification. Our approach, termed B race B ind , allows selecting, at runtime, between actual physical processes or simulations of them to support a running CPS application. To build B race B ind , we create a real-time simulation architecture to generate and manage multiple real-time simulation environments based on existing simulation models in a manner that ensures sufficient accuracy for verifying a CPS application. Specifically, B race B ind aims to both improve simulation speed and minimize latency, thereby making it feasible to integrate simulations of physical processes into the running CPS application. B race B ind then integrates this real-time simulation architecture with an existing runtime verification approach that has low computational overhead and high accuracy. This integration uses an aspect-oriented adapter architecture that connects the variables in the cyber portion of the CPS application with either sensors and actuators in the physical world or the automatically generated real-time simulation. Our experimental results show that, with a negligible performance penalty, our approach is both efficient and effective in detecting program errors that are otherwise only detectable in a physical deployment.

Funder

China Postdoctoral Science Foundation

National Science Foundation

National Natural Science Foundation of China

Publisher

Association for Computing Machinery (ACM)

Subject

Hardware and Architecture,Software

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2. A Review of Real Time Digital Simulations: Theory and Applications for the Energy Transition;IEEE Latin America Transactions;2022-10

3. Investigating the Prospect of Leveraging Blockchain and Machine Learning to Secure Vehicular Networks: A Survey;IEEE Transactions on Intelligent Transportation Systems;2022-02

4. Real-Time Simulation Support for Real-Time Systems;Handbook of Real-Time Computing;2022

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