MoDeS3: Model-Based Demonstrator for Smart and Safe Cyber-Physical Systems

Vörös, András; Búr, Márton; Ráth, István; Horváth, Ákos; Micskei, Zoltán; Balogh, László; Hegyi, Bálint; Horváth, Benedek; Mázló, Zsolt; Varró, Dániel

doi:10.1007/978-3-319-77935-5_31

Cited by 10 publications

(10 citation statements)

References 13 publications

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“…Running Example. We illustrate our runtime monitoring technique in the context of a CPS demonstrator [45], which is an educational platform of a model railway system that prevents trains from collision and derailment using safety monitors. The railway track is equipped with several sensors (cameras, shunt detectors) capable of sensing trains on a particular segment of a track connected to some computing units, such as Arduinos, Raspberry Pis, BeagleBone Blacks (BBB), or a cloud platform.…”

Section: Overview Of Distributed Runtime Monitoringmentioning

confidence: 99%

“…Then we discuss how graph queries can be deployed as a service to the computing units (i.e., low-memory embedded devices) of the execution platform of the system in a distributed way, and provide precise semantics of distributed graph query evaluation over our distributed runtime model. We provide an initial performance evaluation of our distributed query technique over the MoDeS3 CPS demonstrator [45], which is an open source educational platform, and also compare its performance to an open graph query benchmark [35]. Figure 1 is an overview of distributed runtime monitoring of CPSs deployed over heterogeneous computing platform using runtime models and graph queries.…”

Section: Introductionmentioning

confidence: 99%

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Distributed Graph Queries for Runtime Monitoring of Cyber-Physical Systems

Búr

Szilágyi

Vörös

et al. 2018

Fundamental Approaches to Software Engineering

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In safety-critical cyber-physical systems (CPS), a service failure may result in severe financial loss or damage in human life. Smart CPSs have complex interaction with their environment which is rarely known in advance, and they heavily depend on intelligent data processing carried out over a heterogeneous computation platform and provide autonomous behavior. This complexity makes design time verification infeasible in practice, and many CPSs need advanced runtime monitoring techniques to ensure safe operation. While graph queries are a powerful technique used in many industrial design tools of CPSs, in this paper, we propose to use them to specify safety properties for runtime monitors on a high-level of abstraction. Distributed runtime monitoring is carried out by evaluating graph queries over a distributed runtime model of the system which incorporates domain concepts and platform information. We provide a semantic treatment of distributed graph queries using 3-valued logic. Our approach is illustrated and an initial evaluation is carried out using the MoDeS3 educational demonstrator of CPSs.

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Section: Overview Of Distributed Runtime Monitoringmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Distributed Graph Queries for Runtime Monitoring of Cyber-Physical Systems

Búr

Szilágyi

Vörös

et al. 2018

Fundamental Approaches to Software Engineering

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“…We demonstrate the development of component-based reactive systems in the Gamma framework in the context of the MoDeS 3 (Model-based Demonstrator for Smart and Safe Systems) [12] project. 7 The project incorporates a model railway consisting of track elements, such as sections and turnouts, and several trains moving on the track.…”

Section: Running Examplementioning

confidence: 99%

Mixed-semantics composition of statecharts for the component-based design of reactive systems

et al. 2020

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The increasing complexity of reactive systems can be mitigated with the use of components and composition languages in model-driven engineering. Designing composition languages is a challenge itself as both practical applicability (support for different composition approaches in various application domains), and precise formal semantics (support for verification and code generation) have to be taken into account. In our Gamma Statechart Composition Framework, we designed and implemented a composition language for the synchronous, cascade synchronous and asynchronous composition of statechart-based reactive components. We formalized the semantics of this composition language that provides the basis for generating composition-related Java source code as well as mapping the composite system to a back-end model checker for formal verification and model-based test case generation. In this paper, we present the composition language with its formal semantics, putting special emphasis on design decisions related to the language and their effects on verifiability and applicability. Furthermore, we demonstrate the design and verification functionality of the composition framework by presenting case studies from the cyber-physical system domain.

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“…As such, message delivery is guaranteed at a lower abstraction layer-but in a time-triggered protocol, late message delivery still needs to be handled as potential message loss. -Deployment to edge devices Our graph query and manipulation middleware is thin; thus, our runtime models can be deployed over embedded or edge devices such as in the context of the MoDeS3 CPS demonstrator [65] or DDS applications. -Scalability Furthermore, we carried out an initial scalability evaluation of our prototype in the context of the MoDeS3 demonstrator (as a physical CPS platform) and a simulated environment with increasing number of participants.…”

Section: -Distributed Graph Model With Single Source Of Truthmentioning

confidence: 99%

“…We illustrate distributed runtime models and query-based monitoring in the context of the Model-Based Demonstrator for Smart and Safe Cyber-Physical Systems (MoDeS3) [65], which is an educational platform of a model railway system that prevents trains from collision and derailment using safety monitors. The railway track is equipped with several sensors (cameras, shunt detectors) capable of sensing trains on a particular segment of a track connected to some participants realized by various computing units, such as Arduinos, Raspberry Pis, BeagleBone Blacks or a cloud platform.…”

Section: Examplementioning

confidence: 99%

Distributed graph queries over models@run.time for runtime monitoring of cyber-physical systems

Búr

Szilágyi

Vörös

et al. 2019

Int J Softw Tools Technol Transfer

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Smart cyber-physical systems (CPSs) have complex interaction with their environment which is rarely known in advance, and they heavily depend on intelligent data processing carried out over a heterogeneous and distributed computation platform with resource-constrained devices to monitor, manage and control autonomous behavior. First, we propose a distributed runtime model to capture the operational state and the context information of a smart CPS using directed, typed and attributed graphs as high-level knowledge representation. The runtime model is distributed among the participating nodes, and it is consistently kept up to date in a continuously evolving environment by a time-triggered model management protocol. Our runtime models offer a (domain-specific) model query and manipulation interface over the reliable communication middleware of the Data Distribution Service (DDS) standard widely used in the CPS domain. Then, we propose to carry out distributed runtime monitoring by capturing critical properties of interest in the form of graph queries, and design a distributed graph query evaluation algorithm for evaluating such graph queries over the distributed runtime model. As the key innovation, our (1) distributed runtime model extends existing publish-subscribe middleware (like DDS) used in real-time CPS applications by enabling the dynamic creation and deletion of graph nodes (without compile time limits). Moreover, (2) our distributed query evaluation extends existing graph query techniques by enabling query evaluation in a real-time, resource-constrained environment while still providing scalable performance. Our approach is illustrated, and an initial scalability evaluation is carried out on the MoDeS3 CPS demonstrator and the open Train Benchmark for graph queries. Keywords Runtime monitoring • Graph queries • Distributed model management • Data Distribution Service (DDS) 1 Introduction Motivation A smart and safe cyber-physical system [18,38, 39,49,56] (CPS) is a software-intensive decentralized system that autonomously perceives its operational context B András Vörös

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MoDeS3: Model-Based Demonstrator for Smart and Safe Cyber-Physical Systems

Cited by 10 publications

References 13 publications

Distributed Graph Queries for Runtime Monitoring of Cyber-Physical Systems

Distributed Graph Queries for Runtime Monitoring of Cyber-Physical Systems

Mixed-semantics composition of statecharts for the component-based design of reactive systems

Distributed graph queries over models@run.time for runtime monitoring of cyber-physical systems

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