Similar articles

Abstract: cyber-physical systems (CPSs) have emerged as a potential enabling technology to handle the challenges in social and economic sustainable development. Since it was proposed in 2006, intensive research has been conducted, showing that the construction of a CPS is a hard and complex engineering process due to the nature of integrating a large number of heterogeneous subsystems. Among other approaches to dealing with the complex design issues, model-driven design of CPSs has shown its advantages. In this review paper, we present a survey of research on model-driven development of CPSs. We are concerned mainly with the widely used methods, techniques, and tools, and discuss how these are applied to CPSs. We also present comparative analyses on the surveyed techniques and tools from various perspectives, including their modeling languages, functionalities, and the challenges which they address in CPS design. With our understanding of the surveyed methods, we believe that model-driven approaches are an inevitable choice in building CPSs and further research effort is needed in the development of model-driven theories, techniques, and tools. We also argue that a unified modeling platform is needed. Such a platform would benefit research in the academic community and practical development in industry, and improve the collaboration between these two communities.

信息物理融合系统的模型驱动构建技术与工具综述

[1]Abrial JR, 2005. The B-Book: Assigning Programs to Meanings. Cambridge University Press, Cambridge, UK.

[2]Abrial JR, Butler M, Hallerstede S, et al., 2010. Rodin: an open toolset for modelling and reasoning in Event-B. Int J Softw Tools Technol Transfer, 12(6):447-466.

[3]Amrani M, Lucio L, Selim G, et al., 2012. A tridimensional approach for studying the formal verification of model transformations. Proc IEEE 5^th Int Conf on Software Testing, Verification and Validation, p.921-928.

[4]Banach R, Butler M, Qin SC, et al., 2015. Core Hybrid Event-B I: single Hybrid Event-B machines. Sci Comput Program, 105:92-123.

[5]Banach R, Butler M, Qin SC, et al., 2017. Core Hybrid Event-B II: multiple cooperating Hybrid Event-B machines. Sci Comput Program, 139:1-35.

[6]Banerjee A, Kandula S, Mukherjee T, et al., 2012. BAND-AiDe: a tool for cyber-physical oriented analysis and design of body area networks and devices. ACM Trans Embed Comput Syst, 11(S2):49.

[7]Bernardeschi C, Domenici A, Masci P, 2018. A PVS-Simulink integrated environment for model-based analysis of cyber-physical systems. IEEE Trans Softw Eng, 44(6):512-533.

[8]Bocciarelli P, D’Ambrogio A, Giglio A, et al., 2017. A BPMN extension for modeling cyber-physical-production-systems in the context of Industry 4.0. IEEE 14^th Int Conf on Networking, Sensing and Control, p.599-604.

[9]Booch G, Rumbaugh J, Jacobson I, 1999. The Unified Modeling Language User Guide. Addison Wesley Longman Publishing Co., Inc., USA.

[10]Boronat A, Carsí JA, Ramos I, 2006. Exogenous model merging by means of model management operators. Proc 3^rd Workshop on Software Evolution Through Transformations: Embracing the Change, p.1-19.

[11]Brau G, Navet N, Hugues J, 2017. Heterogeneous models and analyses in the design of real-time embedded systems—an avionic case-study. Proc $25^rm th$ Int Conf on Real-Time Networks and Systems, p.168-177.

[12]Braun W, Casella F, Bachmann B, 2017. Solving large-scale Modelica models: new approaches and experimental results using OpenModelica. Proc 12^th Int Modelica Conf, p.557-563.

[13]Broman D, Lee EA, Tripakis S, et al., 2012. Viewpoints, formalisms, languages, and tools for cyber-physical systems. Proc 6^th Int Workshop on Multi-paradigm Modeling, p.49-54.

[14]Brown AW, 2004. Model driven architecture: principles and practice. Softw Syst Model, 3(4):314-327.

[15]Broy M, Cengarle MV, Geisberger E, 2012. Cyber-physical systems: imminent challenges. In: Calinescu R, Garlan D (Eds.), Large-Scale Complex IT Systems. Development, Operation and Management. Springer, Berlin, p.1-28.

[16]Cabot J, Gogolla M, 2012. Object Constraint Language (OCL): a definitive guide. Proc 12^th Int Conf on Formal Methods for the Design of Computer, Communication, and Software Systems: Formal Methods for Model-Driven Engineering, p.58-90.

[17]Calegari D, Szasz N, 2013. Verification of model transformations: a survey of the state-of-the-art. Electron Notes Theor Comput Sci, 292:5-25.

[18]Chen LP, Babar MA, Nuseibeh B, 2013. Characterizing architecturally significant requirements. IEEE Softw, 30(2):38-45.

[19]Chen X, Liu ZM, 2017. Towards interface-driven design of evolving component-based architectures. In: Hinchey M, Bowen JP, Olderog ER (Eds.), Provably Correct Systems. Springer, Cham, p.121-148.

[20]Cicchetti A, di Ruscio D, Eramo R, et al., 2010. JTL: a bidirectional and change propagating transformation language. Proc 3^rd Int Conf on Software Language Engineering, p.183-202.

[21]Clarke EM, 2008. The birth of model checking. In: Grumberg O, Veith H (Eds.), 25 Years of Model Checking: History, Achievements, Perspectives. Springer, Berlin, p.1-26.

[22]Czarnecki K, Helsen S, 2003. Classification of model transformation approaches. Proc 2^nd OOPSLA Workshop on Generative Techniques in the Context of the Model Driven Architecture, p.1-17.

[23]Derler P, Lee EA, Vincentelli AS, 2012. Modeling cyber-physical systems. Proc IEEE, 100(1):13-28.

[24]Eidson JC, Lee EA, Matic S, et al., 2012. Distributed real-time software for cyber-physical systems. Proc IEEE, 100(1):45-59.

[25]ESTEREL, 2015. Efficient development of safe avionics software with DO-178C objectives using SCADE Suite^®. ESTEREL Technologies. http://www.peraglobal.com/upload/contents/2015/11/20151113142739_85462.pdf [Accessed on Aug. 30, 2020].

[26]Feiler PH, Gluch DP, Hudak JJ, 2006. The Architecture Analysis & Design Language (AADL): an introduction. Software Engineering Institute, p.145.

[27]Fowler M, 2003. UML Distilled: a Brief Guide to the Standard Object Modeling Language (3^rd Ed.). Addison-Wesley, Boston, USA.

[28]Friedenthal S, Moore A, Steiner R, 2015. A Practical Guide to SysML: the Systems Modeling Language. Elsevier, Waltham, USA.

[29]Fritzson P, 2014. Principles of Object Oriented Modeling and Simulation with Modelica 3.3: a Cyber-Physical Approach. John Wiley & Sons, Inc.

[30]Fulton N, Mitsch S, Quesel JD, et al., 2015. KeYmaera X: an axiomatic tactical theorem prover for hybrid systems. Proc 25^th Int Conf on Automated Deduction, p.527-538.

[31]Gill H, 2008. From Vision to Reality: Cyber-Physical Systems. http://labs.ece.uw.edu/nsl/aar-cps/Gill_HCSS_Transportation_Cyber-Physical_Systems_2008.pdf [Accessed on Aug. 30, 2020].

[32]Gunes V, Peter S, Givargis T, et al., 2014. A survey on concepts, applications, and challenges in cyber-physical systems. KSII Trans Int Inform Syst, 8(12):4242-4268.

[33]Halbwachs N, Caspi P, Raymond P, et al., 1991. The synchronous data flow programming language LUSTRE. Proc IEEE, 79(9):1305-1320.

[34]He JF, Li Q, 2017. A hybrid relational modelling language. In: Gibson-Robinson T, Hopcroft P, Lazić R (Eds.), Concurrency, Security, and Puzzles: Essays Dedicated to Andrew William Roscoe on the Occasion of His 60^th Birthday. Springer, Cham, p.124-143.

[35]Hehenberger P, Vogel-Heuser B, Bradley D, et al., 2016. Design, modelling, simulation and integration of cyber physical systems: methods and applications. Comput Ind, 82:273-289.

[36]Henriksson D, Elmqvist H, 2011. Cyber-physical systems modeling and simulation with Modelica. Proc 8^th Int Modelica Conf, p.502-509.

[37]Henzinger TA, 1996. The theory of hybrid automata. Proc 11^th Annual IEEE Symp on Logic in Computer Science, p.278-292.

[38]Huang P, Jiang KQ, Guan CL, et al., 2018. Towards modeling cyber-physical systems with SysML/MARTE/ pCCSL. IEEE 42^nd Annual Computer Software and Applications Conf, p.264-269.

[39]J'ez'equel JM, Barais O, Fleurey F, 2009. Model driven language engineering with Kermeta. Proc 3^rd Int Summer School Conf on Generative and Transformational Techniques in Software Engineering III, p.201-221.

[40]Jirkovský V, Obitko M, Mavřík V, 2017. Understanding data heterogeneity in the context of cyber-physical systems integration. IEEE Trans Ind Inform, 13(2):660-667.

[41]Jouault F, Bézivin J, 2006. KM3: a DSL for metamodel specification. Proc 8^th IFIP WG 6.1 Int Conf on Formal Methods for Open Object-Based Distributed Systems, p.171-185.

[42]Jouault F, Allilaire F, Bézivin J, et al., 2008. ATL: a model transformation tool. Sci Comput Program, 72(1-2):31-39.

[43]Juric MB, Mathew B, Sarang P, 2004. Business Process Execution Language for Web Services: BPEL and BPEL4WS. Packt Publishing.

[44]Kleppe A, Warmer J, Bast W, 2003. MDA Explained: the Model Driven Architecture: Practice and Promise. Addison-Wesley, Boston.

[45]Kühne T, 2006. Matters of (meta-) modeling. Softw Syst Model, 5(4):369-385.

[46]Larson BR, Chalin P, Hatcliff J, 2013. BLESS: formal specification and verification of behaviors for embedded systems with software. Proc 5^th Int Symp on NASA Formal Methods, p.276-290.

[47]Lasnier G, Cardoso J, Siron P, et al., 2013. Distributed simulation of heterogeneous and real-time systems. Proc IEEE/ACM 17^th Int Symp on Distributed Simulation and Real Time Applications, p.55-62.

[48]Lawley M, Steel J, 2005. Practical declarative model transformation with Tefkat. MoDELS Int Workshops Doctoral Symp, p.139-150.

[49]Lee EA, 2008. Cyber physical systems: design challenges. Int Symp on Object/Component/Service-Oriented Real-Time Distributed Computing. http://chess.eecs.berkeley.edu/pubs/427.html

[50]Lee EA, 2010. CPS foundations. Proc 47^th Design Automation Conf, p.737-742. http://chess.eecs.berkeley.edu/pubs/804.html

[51]Lee EA, 2018. Modeling in engineering and science. Commun ACM, 62(1):35-36.

[52]Lee EA, Zheng HY, 2005. Operational semantics of hybrid systems. Proc 8^th Int Workshop on Hybrid Systems: Computation and Control, p.25-53.

[53]Lee EA, Niknami M, Nouidui TS, et al., 2015. Modeling and simulating cyber-physical systems using CyPhySim. Proc 20^th Int Conf on Embedded Software, p.115-124.

[54]Lee J, Bagheri B, Kao HA, 2015. A cyber-physical systems architecture for Industry 4.0-based manufacturing systems. Manuf Lett, 3:18-23.

[55]Leino KRM, 2007. Verification of Object-Oriented Software. The KeY Approach. Springer, Berlin.

[56]Liu J, Lv JD, Quan Z, et al., 2010. A calculus for hybrid CSP. Proc 8^th Asian Symp on Programming Languages and Systems, p.1-15.

[57]Liu J, Li TF, Ding ZH, et al., 2019. AADL+: a simulation-based methodology for cyber-physical systems. Front Comput Sci, 13(3):516-538.

[58]Liu Y, Peng Y, Wang BL, et al., 2017. Review on cyber-physical systems. IEEE/CAA J Autom Sin, 4(1):27-40.

[59]Liu ZM, Chen X, 2016. Model-driven design of object and component systems. Engineering Trustworthy Software Systems, Cham, p.152-255.

[60]Liu ZM, Bowen JP, Liu B, et al., 2019. Software abstractions and human-cyber-physical systems architecture modelling. 5^th Int School on Engineering Trustworthy Software Systems, p.159-219.

[61]Lunel S, Mitsch S, Boyer B, et al., 2019. Parallel composition and modular verification of computer controlled systems in differential dynamic logic. In: Ter Beek M, McIver A, Oliveira J (Eds.), Formal Methods—The Next 30 Years. Springer, Cham, p.354-370.

[62]Lynch N, Segala R, Vaandrager F, 2003. Hybrid I/O automata. Inform Comput, 185(1):105-157.

[63]Maler O, Manna Z, Pnueli A, 1992. From timed to hybrid systems. In: de Bakker JW, Huizing C, de Roever WP, et al. (Eds.), Real-Time: Theory in Practice. Springer, Berlin, p.447-484.

[64]Mallet F, 2015. MARTE/CCSL for modeling cyber-physical systems. In: Drechsler R, Kühne U (Eds.), Formal Modeling and Verification of Cyber-Physical Systems. Springer Vieweg, Wiesbaden, p.26-49.

[65]Mallet F, Villar E, Herrera F, 2017. MARTE for CPS and CPSoS: present and future, methodology and tools. In: Nakajima S, Talpin JP, Toyoshima M, et al. (Eds.), Cyber-Physical System Design from an Architecture Analysis Viewpoint. Springer, Singapore, p.81-108.

[66]Mellor SJ, 2004. MDA Distilled: Principles of Model-Driven Architecture. Addison-Wesley, Boston. http://cds.cern.ch/record/1505924 [Accessed on Aug. 30, 2020].

[67]Mens T, van Gorp P, 2006. A taxonomy of model transformation. Electron Notes Theor Comput Sci, 152:125-142.

[68]Miller J, Mukerji J, 2003. MDA Guide Version 1.0.1. Object Management Group.

[69]Mohamed MA, Challenger M, Kardas G, 2020. Applications of model-driven engineering in cyber-physical systems: a systematic mapping study. J Comput Lang, 59:100972.

[70]Müller A, Mitsch S, Retschitzegger W, et al., 2016. A component-based approach to hybrid systems safety verification. In: Ábrahám E, Huisman M (Eds.), Integrated Formal Methods. Springer, Cham, p.441-456.

[71]Nazari S, Sonntag C, Engell S, 2015. A Modelica-based modeling and simulation framework for large-scale cyber-physical systems of systems. IFAC-PapersOnLine, 48(1):920-921.

[72]Oldevik J, Neple T, Gronmo R, et al., 2005. Toward standardised model to text transformations. Proc 1^st European Conf on Model Driven Architecture: Foundations and Applications, p.239-253.

[73]Platzer A, 2008. Differential dynamic logic for hybrid systems. J Autom Reason, 41(2):143-189.

[74]Platzer A, 2010. Logical Analysis of Hybrid Systems: Proving Theorems for Complex Dynamics. Springer, Berlin.

[75]Platzer A, 2018. Logical Foundations of Cyber-Physical Systems. Springer, Cham.

[76]Ptolemaeus C, 2014. System Design, Modeling, and Simulation Using Ptolemy II. http://ptolemy.org/books/Systems [Accessed on Aug. 30, 2020].

[77]Qin ZJ, Do N, Denker G, et al., 2014. Software-defined cyber-physical multinetworks. Int Conf on Computing, Networking and Communications, p.322-326.

[78]Rahim LA, Whittle J, 2015. A survey of approaches for verifying model transformations. Softw Syst Model, 14(2):1003-1028.

[79]Rajkumar R, Lee I, Sha L, et al., 2010. Cyber-physical systems: the next computing revolution. Design Automation Conf, p.731-736.

[80]Saeedloei N, Gupta G, 2016. A methodology for modeling and verification of cyber-physical systems based on logic programming. ACM SIGBED Rev, 13(2):34-42.

[81]Sangiovanni-Vincentelli A, Damm W, Passerone R, 2012. Taming Dr. Frankenstein: contract-based design for cyber-physical systems. Eur J Contr, 18(3):217-238.

[82]Seidewitz E, 2003. What models mean. IEEE Softw, 20(5): 26-32.

[83]Selic B, 2003. The pragmatics of model-driven development. IEEE Softw, 20(5):19-25.

[84]Selić B, Gérard S, 2014. Modeling and Analysis of Real-Time and Embedded Systems with UML and MARTE. Elsevier, Amsterdam.

[85]Sha L, Gopalakrishnan S, Liu X, et al., 2008. Cyber-physical systems: a new frontier. Int Conf on Sensor Networks, Ubiquitous, and Trustworthy Computing, p.1-9.

[86]Simko G, Levendovszky T, Maroti M, et al., 2014. Towards a theory for cyber-physical systems modeling. Proc 4^th ACM SIGBED Int Workshop on Design, Modeling, and Evaluation of Cyber-Physical Systems, p.56-61.

[87]Tan Y, Vuran MC, Goddard S, 2009. Spatio-temporal event model for cyber-physical systems. Proc 29^th IEEE Int Conf on Distributed Computing Systems Workshops, p.44-50.

[88]Tariq MU, Grijalva S, Wolf M, 2015. A service-oriented, cyber-physical reference model for smart grid. In: Khaitan SK, McCalley JD, Liu CC (Eds.), Cyber Physical Systems Approach to Smart Electric Power Grid. Springer, Berlin, p.25-42.

[89]The Object Management Group, 2000. Meta-data Interchange (XMI) Specification. https://www.omg.org/spec/QVT/1.0/PDF [Accessed on Aug. 30, 2020].

[90]The Object Management Group, 2006. Model Driven Architecture. http://www.omg.org/mda/ [Accessed on Aug. 30, 2020].

[91]The Object Management Group, 2008. Meta Object Facility (MOF) 2.0 Query/View/Transformation Specification. https://www.omg.org/spec/QVT/1.0/PDF [Accessed on Aug. 30, 2020].

[92]The Object Management Group, 2013. Business Process Model and Notation (BPMN) Version 2.0.2.

[93]Tratt L, 2005. Model transformations and tool integration. Softw Syst Model, 4(2):112-122.

[94]Varró D, Balogh A, 2007. The model transformation language of the VIATRA2 framework. Sci Comput Program, 68(3):214-234.

[95]Varró D, Pataricza A, 2003. VPM: a visual, precise and multilevel metamodeling framework for describing mathematical domains and UML (The Mathematics of Metamodeling is Metamodeling Mathematics). Softw Syst Model, 2(3):187-210.

[96]Wang BB, Baras JS, 2013. HybridSim: a modeling and co-simulation toolchain for cyber-physical systems. 17^th IEEE/ACM Int Symp on Distributed Simulation and Real Time Applications, p.33-40.

[97]Wang J, Zhan NJ, Feng XY, et al., 2019. Overview of formal methods. J Softw, 30(1):33-61 (in Chinese).

[98]Wang SL, Zhan NJ, Zou L, 2015. An improved HHL prover: an interactive theorem prover for hybrid systems. Proc 17^th Int Conf on Formal Engineering Methods on Formal Methods and Software Engineering, p.382-399.

[99]Wang TX, Truptil S, Benaben F, 2017. An automatic model-to-model mapping and transformation methodology to serve model-based systems engineering. Inform Syst E-Bus Manag, 15(2):323-376.

[100]W3C, 1999. W3C Recommendation. https://www.w3.org/TR/1999/REC-xslt-19991116

[101]Xue B, She ZK, Easwaran A, 2016. Under-approximating backward reachable sets by polytopes. Proc 28^th Int Conf on Computer Aided Verification, p.457-476.

[102]Xue B, Mosaad PN, Fränzle M, et al., 2017. Safe over- and under-approximation of reachable sets for delay differential equations. 15^th Int Conf on Formal Modeling and Analysis of Timed Systems, p.97-115.

[103]Younes AB, Hlaoui YB, Ayed LJB, 2014. A meta-model transformation from UML activity diagrams to Event-B models. Proc IEEE 38^th Int Computer Software and Applications Conf Workshops, p.740-745.

[104]Zhan NJ, Wang SL, Zhao HJ, 2016. Formal Verification of Simulink/Stateflow Diagrams: a Deductive Approach. Springer, Cham, p.1-258.

[105]Zhang LC, Feng SG, 2014. Aspect-oriented QoS modeling of cyber-physical systems by the extension of architecture analysis and design language. Proc Int Conf on Computer Engineering and Network, p.1125-1131.