Advertisement

Model Development and Execution Process with Repositories, Validation, and Verification

  • Bernard P. ZeiglerEmail author
  • Hessam S. Sarjoughian
Chapter
Part of the Simulation Foundations, Methods and Applications book series (SFMA)

Abstract

Model Development and Execution Process with Repositories, Validation, and Verification In this chapter, we discuss another modeling and simulation environment that supports both development and storage of families of DEVS models for Systems of Systems. Component-based System Modeler (CoSMo) is grounded in a unified logical, persistence, and visual model development concept. We show how you can develop; store, retrieve, and instantiate DEVS SoS models such as those for service oriented and cloud systems (Chaps.  14 and  15). We develop a unified concept supporting logical, visual, and persistence modeling and simulation framework (CoSMoS) which lends itself for data (XML Schema) modeling and XML Schema code as well as cellular automata modeling. We show how the concept of SW/HW co-design for systems of systems fits seamlessly into the CoSMoS framework. While being based on the same underlying concepts of DEVS model construction, MS4 Me™ and CoSMoS offer somewhat different perspectives on support for SoS model construction.

References

  1. Alshareef, A., & Sarjoughian, H. S. (2017). DEVS specification for modeling and simulation of the UML activities. In Spring Simulation Multi-Conference, April. Virginia Beach, VA.Google Scholar
  2. CoSMoS (2015). Component-based system modeler and simulator. Retrieved from http://sourceforge.net/projects/cosmosim/.
  3. DEVS-Suite (2017). DEVS-Suite Simulator. Retrieved from http://devs-suitesim.sourceforge.net.
  4. Elamvazhuthi, V. (2008). Visual component-based system modeling with automated simulation data collection and observation. School of Computing, Information, and Decision Systems Engineering, Arizona State University, Tempe, AZ, USA.Google Scholar
  5. Fard, M., & Sarjoughian, H. S. (2015). Visual and persistence behavior modeling for DEVS. In TMS/DEVS Symposium, Spring Simulation Multi-Conference, April. DC: Wash.Google Scholar
  6. Fu, T.-S. (2002). Hierarchical modeling of large-scale systems using relational databases. Master’s Thesis, Department of Electrical and Computer Engineering, University of Arizona, AZ, USA.Google Scholar
  7. Gholami S., & Sarjoughian, H. S. (2017). Modeling and verification of network-on-chip using constrained-DEVS. In TMS/DEVS Symposium, Spring Simulation Multi-Conference, April. Virginia Beach, VA.Google Scholar
  8. Hild, D. R., Sarjoughian, H. S., & Zeigler, B. P. (2001). DEVS-DOC: a modeling and simulation environment enabling distributed codesign. IEEE SMC Transactions-Part A, 32(1), 78–92.Google Scholar
  9. Hu, W. (2007). Visual and persistent co-design modeling for network systems. PhD Thesis, School of Computing, Information, and Decision Systems Engineering, Arizona State University, Tempe, AZ, USA.Google Scholar
  10. Hu, W., & Sarjoughian, H. S. (2007). A co-design modeling approach for computer network systems. In Winter Simulation Conference, Washington DC, USA, December (pp. 685–693).Google Scholar
  11. Hwang, M. H., & Zeigler, B. P. (2006). A modular verification framework using finite and deterministic DEVS. In Proceedings of the DEVS Symposium, Spring Simulation Multi-Conference, Huntsville, Alabama, USA (pp 57–65). Retrieved from https://acims.asu.edu/).
  12. Kim, S., Sarjoughian, H. S., & Elamvazuthi, V. (2009). DEVS-suite: A simulator for visual experimentation and behavior monitoring. In High performance computing & simulation symposium, proceedings of the spring simulation conference, San Diego, CA, USA, 1–7 March.Google Scholar
  13. Sargent, Robert G. (2005). “Verification and validation of simulation models.” Proceedings of the 37th Winter Simulation Conference. 130–143.Google Scholar
  14. Sarjoughian, H. S. (2005). A scaleable component-based modeling environment supporting model validation. In Interservice/industry training, simulation, and education conference, Orlando, FL, USA (pp. 1–11).Google Scholar
  15. Sarjoughian, H. S., & Flasher, R. (2007). System modeling with mixed object and data models. In DEVS Symposium, Spring Simulation Multi-conference, Norfolk, VA, USA, April (pp. 199–206).Google Scholar
  16. Sarjoughian, H. S., & Elamvazhuthi, V. (2009). CoSMoS: a visual environment for component-based modeling, experimental design, and simulation. In 2nd International ICST Conference on Simulation Tools and Techniques, SIMUTools, Rome, Italy, 1–9 March.Google Scholar
  17. Sarjoughian, H. S., Sarkar, S., & Mayer, G. R. (2010). A novel visual CA modeling approach and its realization in CoSMoS. In Spring Simulation Conference, Orlando, FL, USA (pp. 67–70).Google Scholar
  18. Sarjoughian, H. S., Nutaro, J., & Joshi, G. (2011). Towards collaborative component-based modeling. Journal of Simulation, 5(2), 77–88.CrossRefGoogle Scholar
  19. Whitner, Richard B., and Osman Balci. (1989). “Guidelines for selecting and using simulation model verification techniques.” Proceedings of the 21st Winter Simulation Conference. 559–568.Google Scholar
  20. Zeigler, B. P. (1984). Multifaceted modelling and discrete event simulation. San Diego: Academic Press.zbMATHGoogle Scholar
  21. Zeigler, B. P., & Hammonds, P. E. (2007). Modeling & simulation-based data engineering: introducing pragmatics into ontologies for net-centric information exchange. San Diego: Academic Press.Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.University of ArizonaTucsonUSA
  2. 2.Faculty of Computer Science and Computer Systems EngineeringArizona State University, School of Computing, Informatics, and Decision Systems EngineeringTempeUSA

Personalised recommendations