Service-Based Software Systems

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


The goal of this chapter is to show the characteristics of service-based software systems as systems of systems, and how their simulation counterparts can be developed using a DEVS modeling approach. We show how standards such as Service-Oriented Architecture (SOA) play key roles in developing simulation models that are better equipped to be interchanged with their real counterparts. Generic SOA-compliant DEVS model components are developed to closely represent their real counterparts and are used to develop simulation instances of real service-based software systems. Users can systematically and efficiently prototype service-based software systems in simulated settings with capability to evaluate their quality of service attributes such as timeliness and accuracy.


  1. Barros, F. (1997). Modeling formalisms for dynamic structure systems. ACM Transactions on Modeling and Computer Simulation, 7(4), 501–515.CrossRefzbMATHGoogle Scholar
  2. DEVS-Suite (2017). DEVS-Suite Simulator. Retrieved from
  3. Erl, T. (2006). Service-oriented architecture concepts, technology and design. New York: Prentice Hall.Google Scholar
  4. Hu, X., Zeigler, B. P., & Mittal, S. (2005). Variable structure in DEVS component-based modeling and simulation. Simulation, 81(2), 91–102.CrossRefGoogle Scholar
  5. 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, 1–7 March, San Diego, CA.Google Scholar
  6. Kim, S. (2008). Simulator for service-based software system: design and implementation with DEVS-suite. Master’s Thesis, School of Computing, Information, and Decision Systems Engineering, Arizona State University, Tempe, AZ.Google Scholar
  7. Lenz, G., & Moeller, T. (2003). NET: A complete development cycle. Reading: Addison-Wesley.Google Scholar
  8. Møller, A., & Schwartzbach, M. I. (2006). An introduction to XML and web technologies. Reading: Addison-Wesley.Google Scholar
  9. Muqsith, M. A., Sarjoughian, H. S., Huang, D., & Yau, S. S. (2011). Simulating adaptive service-oriented software systems. Simulation, 87(11), 915–931.CrossRefGoogle Scholar
  10. Papazoglou, M. P. (2003). Service-oriented computing: Concepts, characteristics and directions. In WISE (pp. 3–12).Google Scholar
  11. Russell, N., Hofstede, A., Aalst, W., & Mulyar, N. (2006). Workflow control-flow patterns: A revised view. BPM Center Report BPM-06-22.Google Scholar
  12. Sarjoughian, H. S., Kim, S., Ramaswamy, M., & Yau, S. S. (2008). A simulation framework for service-oriented computing systems. In Proceedings of the Winter Simulation Conference, Miami, FL, USA (pp. 845–853).Google Scholar
  13. Yau, S. S., Ye, N., Sarjoughian, H. S., Huang, D., Roontiva, A., Baydogan, M., et al. (2009). Towards development of adaptive service-based software systems. IEEE Transactions on Services Computing, 2(3), 247–260.CrossRefGoogle Scholar
  14. Zeigler, B. P., Praehofer, H., & Kim, T. G. (2000). Theory of modeling and simulation: Integrating discrete event and continuous complex dynamic systems (2nd ed.). 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