StohMCharts: A Modeling Framework for Quantitative Performance Evaluation of Cyber-Physical-Social Systems

Abstract

Cyber-physical-social systems (CPSS) have recently gained attention from researchers due to their combination of cyber, physical, and social spaces. Modeling and Analysis of Real-Time and Embedded systems (MARTE) is a Unified Modeling Language (UML) extension profile that supports the specification, design, and verification of Real-Time Embedded Systems (RTES). While MARTE Statecharts can assist in describing CPS, it does not model the uncertainty within a CPSS environment. To enhance the accuracy of CPSS analysis, we propose the stohMCharts (stochastic hybrid MARTE statecharts) modelling framework as an extension of MARTE statecharts for modelling and analyzing stochastic hybrid systems. stohMCharts can model CPSS in a unified manner. Additionally, based on the mapping rules and algorithms, we have developed a tool to convert models built in stohMChart language into Networks Stochastic Hybrid Automata (NSHA) which can be verified by statistical model checker UPPAAL-SMC. We demonstrate the efficiency and accuracy of the framework by applying it to one autonomous driving scenarios.