Pitfalls and Remedies in Modeling and Simulation of Cyber Physical Systems

The ever-growing advances in science and technology have led to a rapid increase in the complexity of most engineered systems. Cyber-physical Systems (CPSs) are the result of this technology advancement that involves new paradigms, architectures and functionalities derived from different engineering domains. Due to the nature of CPSs, which are composed of many heterogeneous components that constantly interact one another and with the environment, it is difficult to study, explain hypothesis and evaluate design alternatives without using Modeling and Simulation (M&S) approaches. M&S is increasingly used in the CPS domain with different objectives; however, its adoption is not easy and straightforward but can lead to pitfalls that need to be recognized and addressed. This paper identifies some important pitfalls deriving from the application of M&S approaches to the CPS study and presents remedies, which are already available in the literature, to prevent and face them.

[1]  Alberto Falcone,et al.  Distributed Co-Simulation of Complex Engineered Systems by Combining the High Level Architecture and Functional Mock-up Interface , 2019, Simul. Model. Pract. Theory.

[2]  Sherali Zeadally,et al.  Data Quality Challenges in Cyber-Physical Systems , 2015, JDIQ.

[3]  Tianyuan Xiao,et al.  Modeling and Simulation Framework for Cyber Physical Systems , 2012 .

[4]  Nicole J. Saam,et al.  Introduction: Computer Simulation Validation , 2019, Simulation Foundations, Methods and Applications.

[5]  Fredrik Milani,et al.  Requirement Elicitation Using Business Process Models , 2015, BIR.

[6]  Alberto Falcone,et al.  Representation of grossone-based arithmetic in simulink for scientific computing , 2020, Soft Computing.

[7]  Durk-Jouke van der Zee,et al.  Approaches for simulation model simplification , 2017, 2017 Winter Simulation Conference (WSC).

[8]  C. Beisbart,et al.  Computer Simulation Validation , 2019, Simulation Foundations, Methods and Applications.

[9]  Olivier Dalle,et al.  On reproducibility and traceability of simulations , 2012, Proceedings Title: Proceedings of the 2012 Winter Simulation Conference (WSC).

[10]  Claes Wohlin,et al.  Engineering and Managing Software Requirements , 2005 .

[11]  Margaret L. Loper The Modeling and Simulation Life Cycle Process , 2015 .

[12]  Matthias Meyer,et al.  Typical Pitfalls of Simulation Modeling - Lessons Learned from Armed Forces and Business , 2012, J. Artif. Soc. Soc. Simul..

[13]  Cheng Wang,et al.  Definition and identification of system boundaries of highly automated driving , 2015 .

[14]  Simon J. E. Taylor,et al.  An introduction to developing federations with the High Level Architecture (HLA) , 2017, 2017 Winter Simulation Conference (WSC).

[15]  Didar Zowghi,et al.  Requirements Elicitation: A Survey of Techniques, Approaches, and Tools , 2005 .

[16]  Umut Durak,et al.  Guide to Simlation-Based Disciplines: Advancing our Computational Future , 2017 .

[17]  Alberto Falcone,et al.  A model-driven approach to enable the simulation of complex systems on distributed architectures , 2019, Simul..

[18]  Jack P. C. Kleijnen,et al.  EUROPEAN JOURNAL OF OPERATIONAL , 1992 .

[19]  Alberto Falcone,et al.  Engineering systems by combining BPMN and HLA-based distributed simulation , 2017, 2017 IEEE International Systems Engineering Symposium (ISSE).

[20]  Udo Lindemann,et al.  Structural Complexity Management: An Approach for the Field of Product Design , 2008 .

[21]  W. Marsden I and J , 2012 .

[22]  Margaret L. Loper,et al.  Modeling and Simulation in the Systems Engineering Life Cycle , 2015, Simulation Foundations, Methods and Applications.

[23]  Anders Skoogh,et al.  Data quality problems in discrete event simulation of manufacturing operations , 2018, Simul..

[24]  S. Sastry,et al.  Zeno hybrid systems , 2001 .

[25]  Rajeev Alur,et al.  Principles of Cyber-Physical Systems , 2015 .

[26]  Xianming Shi,et al.  A Novel Approach to Extract Knowledge from Simulation Results , 2002 .

[27]  Svyatoslav Yatsyshyn,et al.  Metrological Array of Cyber-Physical Systems. Part 5. Quality Assurance in Measuring Instrument Design , 2015 .

[28]  J. Carson Introduction to modeling and simulation , 2005, Proceedings of the Winter Simulation Conference, 2005..

[29]  Ata Ullah,et al.  Survey of Requirement Management Techniques for Safety Critical Systems , 2018, 2018 12th International Conference on Mathematics, Actuarial Science, Computer Science and Statistics (MACS).

[30]  Tao Li,et al.  A system boundary identification method for life cycle assessment , 2014, The International Journal of Life Cycle Assessment.